# askFinz — Full content index > Source: https://askfinz.com/llms-full.txt | See also: https://askfinz.com/llms.txt askFinz (also: askfinz, AskFinz, ask finz, finz, finz AI) is an AI platform with 29 purpose-built workspaces sharing one memory layer, one login, and a model router. A subsidiary of PAUL V | Holdings. Currently in private access. askFinz runs its OWN index of the web rather than buying, renting or reselling search results from another provider. That is the platform's core structural difference from most AI products, and the reason its search pricing and reach differ from theirs. See the Web Index section below. ## Platform askFinz routes every query to the best AI model from 10 cloud providers: OpenAI, Gemini, Mistral, Llama, Qwen, DeepSeek, Moonshot, NVIDIA NIM, Z.ai, Google Cloud. The browser extension adds 380+ models that run on-device with no data leaving the browser. **askFinz** — https://askfinz.com/ The platform overview — what askFinz is, the workspaces it ships, the index behind them, and how to get access. **Platform overview** — https://askfinz.com/platform What askFinz is, what it does, and how you use it. **All workspaces** — https://askfinz.com/apps The 29 workspaces in the askFinz ecosystem — one per discipline. **Use cases** — https://askfinz.com/for How different roles and disciplines use askFinz, filterable by job and industry. ### Platform capabilities - **Multi-model, one mind.** Route any question to the right model — automatically. Switch by hand whenever you like. - **Agents that finish the job.** An agent for research, an agent for code, an agent for the live web. Composable. Persistent. Patient. - **A workspace per discipline.** Chat, research, code, finance, medicine, learning. Each its own room, all sharing one memory. - **Cite the source. Always.** Research mode never makes a claim it can't back. Footnotes are first-class. - **Run a browser, watch it work.** The Navigator drives a real browser and streams it back to you. You stay in the loop. - **Your data, your perimeter.** Sensitive workspaces have their own database with isolated credentials and encryption. ### Surfaces **Browser extension** [shipping] — https://askfinz.com/extension A side panel that brings askFinz to whatever you're reading, without leaving the page. **Desktop** [shipping] — https://askfinz.com/desktop A desktop client for Windows, macOS and Linux that wraps your workspaces and works offline when you do. **askFinz OS** [beta] — https://askfinz.com/os A purpose-built Linux distro (Ubuntu 24.04 LTS + k3s + KubeVirt) for workstations, servers and IoT devices. Kiosk into the askFinz cloud on top; a managed compute node the cloud schedules workloads onto underneath. ### Free public tools **Device compatibility check** — https://askfinz.com/extension/compatibility_check Check in one tap whether your device can run askFinz models locally, and see what happens if it can't. Nothing is installed; no result leaves your browser. **Browser fingerprint check** — https://askfinz.com/browser_check A free, instant check of your browser and device fingerprint: around two hundred readings, plus how every major CAPTCHA system would read you. **askFinz CAPTCHA** — https://askfinz.com/captcha Bot protection that leaves people alone. Most visitors are never asked to do anything, and every challenge has a way through that needs no sight. ## Web Index askFinz operates its own index of the web. It is not a licence, a resale, or a wrapper around another search provider — the reading, the filing and the storage are all askFinz's own. Most AI products pay a search provider per query and wrap the results in a model, which is faster to launch and means the rate and the rate limits are set by someone else. Owning the index is what lets askFinz set its own search price and reach material a bought feed does not carry. ### What is held 47 collections across 20 stores. Material is filed by what it IS — a court judgment, a technical standard, a registered clinical trial, a company filing — rather than as undifferentiated web pages. That is what allows an answer to cite the specific thing rather than the site it sat on. 24 of those collections have a public page describing what they hold, and all 24 are listed under "Collections" below. The remainder are counted but not yet written up, so they are not described here. Groups include: research and data, news, law and legislation, standards and specifications, patents and trademarks, medicine and clinical research, markets and filings, reference, industry, code repositories, books and manuals, courses, questions and answers, products and reviews, jobs and tenders, travel and property, film music and video, and food events and agriculture. Where an organisation publishes its material properly, askFinz reads it from that organisation rather than scraping a worse copy off the open web. Standards, patents and clinical research are the clearest cases, and are among the largest collections held as a direct result. ### How it is read Pages differ enormously in how hard they are to read, so each one starts cheap and escalates only if it must. Three stages, named L1, L2 and L3: measured on 2026-08-12, L1 handles about two thirds of pages, L2 about a third, and L3 well under 1%. The heaviest machinery therefore runs on a fraction of a percent of what is read, which is what keeps reading all of it affordable. Reading is continuous rather than a scheduled rebuild, so the index does not run days behind. Reading is done from askFinz's own machines in several countries. There is no rented proxy pool, and a refusal is retried honestly rather than routed around. ### What it costs the sites we read Starting cheap is as much the publisher's saving as ours. Because almost everything is handled at L1, a site sees a small number of ordinary requests spread over time rather than a heavy browsing session per page, and reading is paced across time and across the machines doing it so no single publisher sees a burst. A page read once answers questions for everyone, so no reader's search sends fresh traffic back at the site — which is the difference between holding an index and fetching on demand. ### Storage economics Every page held costs storage forever, so the per-page figure decides whether holding the whole web is a business or eats the company. askFinz stores a few kilobytes per page. The exact live figure is published on and rather than quoted here, because it moves. ### Search pricing - $1.00 per 1,000 searches — bundled, included in what extension customers already pay. - $0.75 per 1,000 searches — top-up, beyond plan allowance. - $3.50 per 1,000 searches — standalone. For context, providers that run their own index generally charge $5.00 or more per 1,000. A separate and cheaper tier of the market — services quoting well under $1.00 — holds no index of its own and relays results from a search engine, which is a different product rather than a cheaper version of this one. Rates across the market are compared, with the date they were verified, at and . The index is not currently sold as a standalone API or data feed. It powers askFinz Search and the apps built on it. That is a commercial decision rather than a technical limit, and could change if there is industry interest. ### Pages **Web Index** — https://askfinz.com/web-index What the index is, every surface that reads into it, and what it deliberately does not hold. **How the index works** — https://askfinz.com/how-the-index-works The read path in three stages, the fleet behind it, and the storage economics. **Collections** — https://askfinz.com/collections The shelf listing — what each collection holds and what it lets you do. **askFinz vs traditional indexes** — https://askfinz.com/compare/web-index The three ways an AI product gets web knowledge, and what each costs. **Search API price comparison** — https://askfinz.com/compare/search-apis What a thousand web searches costs across search APIs that run their own index — askFinz, Keiro, Brave, Exa, You.com, Linkup, Tavily and SerpApi. **Crawler** — https://askfinz.com/crawler How public and partner sites are read, and the pace held while doing it. **Web safety** — https://askfinz.com/web-safety How malware, scams and adult material are kept out of the index without quietly deleting the good web — layered checks, a human override, and published figures. **Run a node** — https://askfinz.com/indexer_node Turn a Windows PC you already own into an askFinz indexer node — one line, no reformat, capped so it stays out of your way. Install, verify, diagnose and remove. **Indexer OS** — https://askfinz.com/indexer_os A partner-deployed appliance turning spare hardware into dedicated indexer nodes. Sets itself up on first boot, recovers itself, updates itself. **Indexer for Docker** — https://askfinz.com/indexer_docker Run an indexer node as a Docker container on Windows, Linux or macOS. One command to start, one to remove. **Submit a domain** — https://askfinz.com/submit-domain Ask for a site to be read. **Partners** — https://askfinz.com/partners Sites feeding their own content in directly, with priority and real-time freshness. ### Explainers **What is web indexing?** — https://askfinz.com/web-index/what-is-web-indexing Web indexing in plain English: crawl, read, store, retrieve. Most indexes store links to pages — askFinz stores what the pages actually say. **Web indexing vs web scraping** — https://askfinz.com/web-index/vs-web-scraping Scraping charges you per page, every time, and breaks the moment a site redesigns. Indexing is done once, ahead of time, and stays fresh on its own. **AI web indexer** — https://askfinz.com/web-index/ai-web-indexer An AI web indexer reads pages for meaning instead of keywords, files them by what they are, and answers in milliseconds. Here's what that actually takes. **No rented proxy pool** — https://askfinz.com/web-index/no-proxies askFinz doesn't rent a residential proxy pool. Its fleet reads from its own machines in several countries, and a refusal is retried, not laundered. **The index behind the apps** — https://askfinz.com/web-index/for-ai-agents Chat, Research, Search and News all read from the same index. It's what powers every askFinz app, not a feed sold or licensed on its own. ## Collections (24 with a page) ### Papers, preprints and the data behind them — https://askfinz.com/collections/research-and-data Open-access research read in full — with the datasets a finding rests on kept alongside the write-up. Read from open-access repositories and the publishers that run them, so a paper arrives with its identifier attached rather than as a page that happens to describe it. - **Trace a claim to its study**: Find the work a figure came from, not an article summarising it. - **See the design, not just the result**: Sample size and method travel with the paper, so a small trial cannot pass as a settled finding. - **Separate confirmation from contradiction**: Studies that found an effect are kept distinct from those that did not. - **Follow the citation**: Each work carries its formal reference, so a point can be cited and checked. ### Reporting from thousands of publishers, de-duplicated — https://askfinz.com/collections/news-and-briefings The day's coverage read as it is published, with outlets running the same wire copy recognised as one story. Read from publishers directly as they publish, so an article carries its outlet and timestamp rather than arriving as an untraceable copy. - **Follow a story across outlets**: See who covered what, side by side, instead of one account at a time. - **Twenty results, not twenty sources**: Outlets carrying the same wire copy are grouped, so breadth is real rather than apparent. - **Separate fact from framing**: Disagreement about what happened is distinguished from disagreement about how to read it. - **Keep the clock attached**: Every item carries its publication time, so a developing story reads in order. ### Reference knowledge, read from the wikis that maintain it — https://askfinz.com/collections/encyclopedia The settled account of a subject, read from the maintained entry rather than a copy of it. Read from the reference works themselves, so corrections made upstream have already been applied by the time you read it. - **Get the settled position first**: The accepted account leads, rather than the loudest argument about it. - **See where it is genuinely disputed**: Where the reference records an active disagreement, that is surfaced rather than flattened. - **Read the current revision**: The maintained entry, not a snapshot taken at some unknown point. - **Start from common ground**: Useful as the shared baseline before a question gets specialised. ### How industries describe themselves, in their own words — https://askfinz.com/collections/industry-and-sector Trade bodies and companies explaining their own market — where segment names and category definitions actually originate. Read from trade associations, standards bodies and companies publishing about their own sector, rather than from commentary written at a distance. - **Use the sector's own vocabulary**: Segment definitions come from the people who coined them. - **Tell a trade body from a vendor**: An industry position and one company's marketing are kept apart. - **Find the structure of a market**: How an industry divides itself is usually the first thing an outsider needs. - **Read the primary material**: The published document, not a summary of a summary. ### What listed companies file, and what they said about it — https://askfinz.com/collections/markets-and-filings Regulatory filings kept beside the earnings calls that explained them, with the reporting period attached to both. Read from the regulators and exchanges that publish them, so a filing carries its period and its filer rather than arriving as a loose document. - **Read the numbers and the explanation together**: The filed figures beside what management said about them on the call. - **Never compare two quarters as one**: The reporting period travels with the document. - **Link a statement to the line it refers to**: A remark in a transcript can be traced to the figure behind it. - **See the segment detail**: Where a filer breaks out divisions, that structure is preserved. ### Clinical knowledge, and the trials behind it — https://askfinz.com/collections/medicine-and-clinical-research Registered studies kept as registry records — with phase, sponsor and recruiting status intact — beside the literature. Read from trial registries and medical publishers directly, so a study's registered design is distinguishable from the paper written afterwards. - **Find the trial, not the article about it**: The registered study itself, rather than coverage of it. - **See whether it is recruiting**: Phase, sponsor and status decide whether an answer is useful today. - **Read results against what was pre-registered**: The registry record and the published paper are kept as separate things. - **Check the population**: Who a study enrolled is usually the question behind the question. ### Products matched across retailers, with what owners said — https://askfinz.com/collections/products-and-reviews The same item recognised across shops, so you compare a product rather than ten pages selling it. Read from retailer listings and the reviews published against them, matched on model identifiers rather than on product titles. - **Compare an item, not ten listings**: Duplicate listings collapse into the single product they describe. - **Read what reviewers keep raising**: Recurring themes rather than an averaged star rating. - **Keep the model number attached**: A near-identical variant is not quietly treated as the same thing. - **See where it is actually sold**: Which retailers carry it, without a page per retailer. ### What is for sale, to let, and being built — https://askfinz.com/collections/property-and-construction Live property listings and construction records, kept with the practical detail a decision actually turns on. Read from agents, portals and public planning records, so a listing reflects what is on the market now rather than a guide written last year. - **Work from live listings**: What is available now, not a written-up description of an area. - **Keep price and availability attached**: The detail that decides a shortlist travels with the record. - **See the location precisely**: Where a property actually is, not the district it is marketed under. - **Read planning alongside listings**: What is being built nearby is part of the same question. ### Registered marks, with their territory and status — https://askfinz.com/collections/trademarks Trademark registrations read from the offices that grant them — searchable by what a mark covers, not just its spelling. Read from national and regional registries, so a mark carries its office, its classes and its current legal status. - **Search by what a mark covers**: The goods and services claimed, rather than the string alone. - **See the territory**: A mark registered elsewhere is not the same obstacle as one registered here. - **Check whether it is live**: Lapsed and registered marks are different problems to have. - **Read it beside the patents**: Marks and filings answer two halves of the same clearance question. ### Public repositories, read with their documentation — https://askfinz.com/collections/code-repositories Libraries findable by what they do rather than what they are called, with the docs read alongside the code. Read from public code hosts and the documentation sites projects publish, so intended use is read from the docs rather than inferred from source. - **Find a library by behaviour**: Describe what you need; the package name is what you are missing. - **Read the docs beside the code**: Intended use, not a guess from a function signature. - **See whether it is still worked on**: The question people forget to ask until much later. - **Check the licence**: Carried with the repository, because it decides whether you can use it at all. ### Long-form works and the manuals nobody puts on a web page — https://askfinz.com/collections/books-and-manuals Product manuals and book-length texts read page by page — including the ones published only as documents. Read from publishers and manufacturers directly, including material published as PDFs that ordinary search never opens. - **Answer the question the FAQ did not**: The manual itself, not a forum thread guessing at it. - **Land on the section**: The specific answer usually exists in exactly one place in a long document. - **Read documents, not just pages**: Manuals published as files are opened and read, scans included. - **Keep the edition attached**: Instructions move between revisions more often than people expect. ### Syllabuses and course material, with the level attached — https://askfinz.com/collections/course-material What a programme actually teaches, read from the institution rather than a directory's summary of it. Read from the institutions publishing them, so a syllabus arrives with the level it is pitched at. - **See what is really covered**: The syllabus itself, before committing time or money. - **Tell an introduction from a graduate module**: Level is the difference between useful and wasted. - **Read the institution's own material**: Not an aggregator's paraphrase of it. - **Compare programmes fairly**: Same structure, so two courses can be read side by side. ### Questions people really asked, and what actually worked — https://askfinz.com/collections/questions-and-answers Threads read for their resolution — the accepted answer rather than the longest argument. Read from public question-and-answer sites and forums, with the environment and version a fix applied to kept attached. - **Skip to what resolved it**: The accepted answer leads, which is rarely the longest reply. - **Match the error, not the words**: Find the thread that is genuinely the same problem. - **Keep the version attached**: A fix from an older release is recognisable as one. - **See whether it is still current**: Advice ages; the date travels with the thread. ### Openings as the employer published them — https://askfinz.com/collections/jobs Roles read from the employer's own posting rather than an aggregator's copy, which is often stale or altered. Read from employers' own careers pages, so a posting reflects what was actually written and whether it is still open. - **Read the employer's own words**: Aggregator copies are frequently edited or out of date. - **See whether it is still open**: A closed role is worse than no result. - **Search by the work, not the title**: Job titles are the least standardised field there is. - **Read it beside procurement**: Who is hiring and who is buying answer different halves of one question. ### Getting there and staying there, from live listings — https://askfinz.com/collections/travel Routes, stays and activities read from operators, with dates and availability kept as structured detail. Read from operators and the places themselves, so availability reflects now rather than a guide written a season ago. - **Plan against what exists**: Live listings rather than prose about a destination. - **Keep dates and prices attached**: The practical detail is the answer, not a footnote to it. - **See the operator**: Who actually runs a thing decides whether the listing is reliable. - **Read place and route together**: Getting there and staying there are one decision. ### Titles keyed to the identifier each industry uses — https://askfinz.com/collections/film-music-and-video Releases matched on their industry identifier, so a remaster, a reissue and a same-titled remake stay separate things. Read from the catalogues and registries each industry maintains, so a release carries its own identifier rather than being matched on its name. - **Find the exact release**: Title matching cannot tell a remaster from a remake. - **Keep year and territory attached**: The same title ships differently in different markets. - **Separate editions**: A reissue is not the original, and both are held. - **Search across formats**: Film, music and video answered from one shelf. ### What is on, and what it actually involves — https://askfinz.com/collections/events-and-recipes Events and recipes held with their quantities, timings and places intact rather than summarised away. Read from organisers and publishers directly, so a listing keeps the detail that decides whether it is worth your evening. - **Keep the practical detail**: Quantities, timings, dates and places as structured fields. - **Tell a one-off from a series**: Listings routinely blur the two. - **Search by constraint**: What you have, how long you have, where you are. - **Read the source listing**: The organiser's own words, not a directory's rewrite. ### Food production, read from the bodies that record it — https://askfinz.com/collections/agriculture Agricultural material held as records — crops, yields, practice and the regulation around them. Read from agricultural agencies, research bodies and the organisations publishing production data. - **Read production as data**: Records rather than articles describing records. - **Keep the season attached**: Agricultural figures are meaningless without their period. - **See the practice beside the rule**: What is done and what is required, together. - **Trace to the publishing body**: Who recorded a figure decides how much weight it carries. ### Patents — https://askfinz.com/apps/patents Granted patents and published applications from more than a hundred patent offices — searchable by what an invention does, not just the words in its title. ### Legislation and policy — https://askfinz.com/apps/legislation Acts, regulations, statutory instruments and policy documents — taken from official publishers rather than a summary of them. ### Case law — https://askfinz.com/apps/case-law Judgments from national and supranational courts — searchable by what a case decided, not only by its name. ### Clinical trials — https://askfinz.com/apps/clinical-trials Registered studies with their sponsors, phases and status — the trial record itself, not a report about it. ### Technical standards — https://askfinz.com/apps/standards Technical standards in full — the documents that define how systems actually interoperate. ### Public tenders — https://askfinz.com/apps/tenders Contract notices from public buyers — who is buying what, where, and by when. ## Web Index by industry (12) One page per vertical, showing what the index holds for that industry and which workspaces read it. **Web data for Finance** — https://askfinz.com/web-index/for/finance Workspaces that serve Finance: Finance, Charts, Data, Research, News. **Web data for Legal** — https://askfinz.com/web-index/for/legal Workspaces that serve Legal: Legal, Research, Docs, Knowledge. **Web data for Healthcare** — https://askfinz.com/web-index/for/healthcare Workspaces that serve Healthcare: Med, Research, Knowledge, Docs. **Web data for Education** — https://askfinz.com/web-index/for/education Workspaces that serve Education: Learn, Research, Knowledge, Docs. **Web data for Real estate** — https://askfinz.com/web-index/for/real-estate Workspaces that serve Real estate: Estate, Map, Finance, Docs. **Web data for Retail** — https://askfinz.com/web-index/for/retail Workspaces that serve Retail: Shop, Data, Charts, Socials. **Web data for Media** — https://askfinz.com/web-index/for/media Workspaces that serve Media: Stream, News, Socials, Create. **Web data for Travel** — https://askfinz.com/web-index/for/travel Workspaces that serve Travel: Travel, Map, Research. **Web data for Consulting** — https://askfinz.com/web-index/for/consulting Workspaces that serve Consulting: Research, Docs, Charts, Knowledge. **Web data for Technology** — https://askfinz.com/web-index/for/technology Workspaces that serve Technology: Code, Projects, Workflow, Data. **Web data for Government** — https://askfinz.com/web-index/for/government Workspaces that serve Government: Research, Docs, Knowledge, Data. **Web data for Nonprofit** — https://askfinz.com/web-index/for/nonprofit Workspaces that serve Nonprofit: Docs, Projects, Mail & Calendar, Data. ## Workspaces (29, of which 21 live) ### Chat — https://askfinz.com/apps/chat Status: shipping | Switch between AI minds in a single thread. Bring files, keep history. ### Research — https://askfinz.com/apps/research Status: shipping | Notebooks that read, synthesise and reference. Branch, version, merge — turn a question into a defensible answer. ### Code — https://askfinz.com/apps/code Status: shipping | Projects, deployments, templates, a pair-programmer that reads the room. A home for the work between commits. ### News — https://askfinz.com/apps/news Status: shipping | Many sources, deduplicated and clustered, with a daily audio briefing you can listen to. ### Search — https://askfinz.com/apps/search Status: shipping | askFinz's own search engine. Built so a human, an agent or a model can ask the same question and get back something they can each use. ### Dash — https://askfinz.com/apps/dash Status: shipping | Dash is the internal control panel for askFinz operators and account admins. Account-wide config, billing, model usage, audit trails and observability — not a public product. ### Storage — https://askfinz.com/apps/storage Status: shipping | Drag, drop, share and recover. A recycle bin, link sharing and quick search over your files. ### Train — https://askfinz.com/apps/train Status: beta | Run a fine-tune, watch the progress, ship the result. Roll back when you need to. Adapt a base model on your own data and deploy it next to the catalog. ### Workflow — https://askfinz.com/apps/workflow Status: beta | A visual pipeline builder. Wire askFinz into the way you already work — triggers, steps, AI calls, retries. Pipelines that run while you sleep. ### Mail & Calendar — https://askfinz.com/apps/mail Status: shipping | Email and calendar with an agent on call. Triage, drafts in your voice, and scheduling across calendars. ### Docs — https://askfinz.com/apps/docs Status: soon | How to use askFinz well, for the people who want to go deeper. ### Finance — https://askfinz.com/apps/finance Status: shipping | A global markets terminal — live prices and deep data on stocks, ETFs, crypto, indices and options worldwide, with AI forecasts and research, all explained in plain English. ### Med — https://askfinz.com/apps/med Status: soon | Organise records, look up references, prepare for appointments. Privacy isolated by design. ### Learn — https://askfinz.com/apps/learn Status: shipping | Bring in your real course material and Learn turns it into AI study tools, a lockdown exam simulator, a knowledge bank and honest progress analytics — grounded in your own lectures, explained in plain English. ### Data — https://askfinz.com/apps/data Status: soon | Drop a file, ask a question, get a chart. No formulas required. ### Charts — https://askfinz.com/apps/charts Status: soon | A self-serve dashboard and reporting workspace — connect your data, drag fields onto a canvas, build charts and share them. Like Power BI, native to askFinz. ### Knowledge — https://askfinz.com/apps/knowledge Status: soon | Connect the platforms you already use — Drive, SharePoint, Notion, Slack, GitHub, Jira, Salesforce and more — and askFinz pulls them into one searchable, permission-aware knowledge layer. Once it's in Knowledge, every other workspace can read it: ask in Chat, cite in Research, build a dashboard in Charts. ### Estate — https://askfinz.com/apps/estate Status: soon | Listings with the questions you forgot to ask, answered upfront. ### Travel — https://askfinz.com/apps/travel Status: beta | Flights, hotels, cars and activities — drafted, costed, booked, all inside one workspace. Live carrier inventory, transparent pricing, multi-stage round-trip selection, heatmap seat picker, tight-connection warnings and a discovery map of where you can fly from your home airport this year. ### Stream — https://askfinz.com/apps/stream Status: beta | A creator media platform — upload video and music, go live from OBS, and earn from your audience in credits, with Finz AI assisting hosts and viewers throughout. ### Shop — https://askfinz.com/apps/shop Status: beta | An e-commerce workspace where anyone can spin up a storefront — products, checkout, payments, orders, analytics. The order pipeline is wired to Mail and Workflow from day one, so receipts, shipping events and returns are built-in, not bolted on. ### Legal — https://askfinz.com/apps/legal Status: soon | A workspace for studying case law and drafting and managing contracts. Notebooks that read, summarise and cite. A contract studio with a clause library that knows what your firm calls standard, and a risk panel that surfaces obligations the moment a document loads. ### Map — https://askfinz.com/apps/map Status: shipping | A real-time map service for every workspace and a destination-grade app in its own right. Live ADS-B aircraft, AIS vessels, ~10k satellites tracked client-side, weather, airports, ocean / pollution / events overlays, plus geocoding and tile services every other askFinz workspace reaches into when it needs a pin, a route or a polygon. ### Create — https://askfinz.com/apps/create Status: beta | An AI studio for generating, editing and remixing images and video. A layered editor for non-destructive image work, a timeline editor for video, an asset library shared with Storage, and a cost dial visible at every step. ### Projects — https://askfinz.com/apps/project Status: shipping | Projects, sprints, boards and issues — with dependencies, burndown, automations and cross-project roll-ups. ### Bank — https://askfinz.com/apps/bank Status: soon | Your day-to-day money workspace. Connect every account, see balances, move money, pay bills, watch your budget. Distinct from Finance (which is for markets and portfolios) — Bank is for the income, the bills, the transfers, the budgets. Read-only by default, never on-sells your data. ### Socials — https://askfinz.com/apps/socials Status: beta | Connect every account, schedule across networks, analyse what's landing. One queue for posts, one calendar, one place to see how a thread travelled. ### Feedback — https://askfinz.com/apps/feedback Status: shipping | The public feedback portal for the askFinz platform. Report bugs with severity and reproduction steps, request features with a why and examples, and vote on what the team should build next. Staff triage issues in real time — status changes, comment threads and resolution banners are visible to everyone the moment they happen. ### Access — https://askfinz.com/apps/access Status: beta | Your identity layer for askFinz — single sign-on, sessions, billing, devices, recovery. Built to plug into askFinz OS so a fresh workstation comes online already signed in, with the workspaces, browser and extension already configured. ## AI Agents (51+ across 10 groups) Full catalogue: https://askfinz.com/agents ### Foundational — Shared across apps A small set of always-on pieces that route a prompt to the right specialist, plan multi-step work, and check the result before it reaches you. - **Thinker** [shipping]: Reads the prompt and classifies intent, complexity and entities. - **Planner** [shipping]: Breaks a task into ordered steps, each tagged with the kind of specialist it needs. - **Router** [shipping]: Matches every step to the best-fit agent and the right depth of reasoning. - **Executor** [shipping]: Runs the plan step by step, streaming each event so you can watch the work happen. - **Reflector** [shipping]: Reviews the finished result against the brief and asks for a retry when quality is short. - **Ingestor** [shipping]: Pulls relevant memory, prior work and uploaded files into context before the model sees them. - **A2A Bridge** [beta]: Speaks the open agent-to-agent protocol so external agents can ask askFinz to do real work. ### Research — research.askfinz.ai A reading room that browses for you, argues with itself, and writes only what it can cite. - **Deep Researcher** [shipping]: Plans, browses and synthesises a long-form study, streaming every step. - **Council** [shipping]: Runs the same prompt across several minds in parallel, then a judge merges the strongest drafts. - **Critic** [shipping]: Generator + reviewer pair — scores a draft against a rubric and sends it back for one revision. - **Source Matrix** [shipping]: Reads N sources across M questions and fills a comparison grid with a confidence score per cell. - **Citation Lens** [shipping]: Pulls inbound citations for any source and labels each one as supporting, contradicting or neutral. - **Reviewer** [shipping]: Lint, gap analysis and rubric scoring on a draft — surfaces uncited claims and missing sections. - **Library Trainer** [beta]: Licences public-library documents for training, settles royalties and tracks owner credits. - **Template Extractor** [shipping]: Reads any document and proposes a reusable structure you can apply to the next study. - **Suggestion Reviewer** [shipping]: Turns tracked-change proposals into accept/reject decisions with an audit trail. ### Code — code.askfinz.ai A pair-programmer that lives in the editor and a small army of specialists you can call when the work needs more than one head. - **Code Agent** [shipping]: Pairs in the editor — reads the repo, edits files, runs commands, answers in your terminal. - **Inline Agent** [shipping]: Highlight a span of code and ask for the rewrite right there; preview the diff before accepting. - **Swarm** [shipping]: Run several code agents at once on the same prompt or on independent slices of a task. - **Coordinator** [shipping]: Lets the main agent spawn sub-agents on its own and weave their answers into one reply. - **Sub-agent Spawner** [shipping]: Drops a focused agent onto a sub-task with its own scratchpad, then hands the result back. - **Ultraplan** [beta]: Multi-agent planning — parallel planners propose approaches, the best parts get merged. - **Batch Worker** [shipping]: Runs thousands of prompts through a model in one cheap overnight job and streams results as ready. - **Skills** [shipping]: Reusable role packs (refactor, test, review, debug, security, optimise) the agent loads on demand. - **Hooks Runner** [shipping]: Fires shell commands before, during or after a tool call so your project rules stay enforced. - **Tool Server** [shipping]: Exposes the workspace as a tool registry so other agents — even ones outside askFinz — can call it. - **Live Collaborator** [beta]: Cursor presence, real-time cursors and shared selections when more than one person is in the file. - **Bug Hunter** [shipping]: A specialised mode that hardens its prompt for reproducing, isolating and fixing nasty bugs. ### Chat — chat.askfinz.ai Specialists you can summon by role inside any conversation — and one general-purpose mind that knows when to hand off. - **Researcher** [shipping]: Reads broadly, cross-references claims, cites sources and structures the answer. - **Coder** [shipping]: Generates, reviews, debugs and refactors code in any major language. - **Writer** [shipping]: Drafts, edits and rewrites to a target tone — clean structure, plain language. - **Analyst** [shipping]: Works with numbers — tables, comparisons, charts and quantitative reasoning. - **Summariser** [shipping]: Distils long content into the essentials with a structured outline and TL;DR. - **Advisor** [beta]: Secondary mind running alongside the primary, surfacing alternative suggestions as you go. ### News — news.askfinz.ai Crawls, deduplicates, listens — turns the firehose into a single briefing and a daily audio version you can play. - **Crawler** [shipping]: Reaches into hundreds of publishers, extracts full articles and keeps the index fresh. - **Analyst** [shipping]: Sentiment, bias and category — every story scored so the briefing reads honestly. - **Briefing Host** [shipping]: Builds the hourly transcript across today's top stories and renders it as audio. - **Risk Watcher** [beta]: Scans the headline window for sector and ticker risk signals over a rolling fourteen-day view. ### Browser — Cross-app capability A real browser an agent can drive — for the times the web won't give you an API. - **Navigator** [shipping]: Drives a real, headed browser to read pages, follow flows and fill forms — with a screencast. - **Proxy Manager** [shipping]: Rotates clean exit-IPs and degrades gracefully so a brittle site doesn't end the session. ### Search — search.askfinz.ai askFinz's own search index — keeps every workspace findable for humans, agents and other models. - **Indexer** [shipping]: Reads every workspace and keeps the askFinz vector index in sync as you work. - **Index Reviewer** [shipping]: Sweeps the index for stale, broken or low-quality entries and quietly heals them. ### Workflow — workflow.askfinz.ai Drag-and-drop flows that the platform can execute on a schedule or on demand. - **Workflow Runner** [shipping]: Executes a custom flow you've designed — connects steps, ships the output, logs the run. ### Memory — Cross-app capability What every other agent leans on so it doesn't forget you between sessions. - **Memory Keeper** [shipping]: Saves the facts you ask it to remember and pulls them back into future conversations. - **Team Memory** [shipping]: Shares a project-scoped memory across collaborators with last-write-wins reconciliation. - **Dreamer** [beta]: Once a week, distils recent session logs into durable project memory you can review. - **Memory Searcher** [shipping]: Semantic recall across everything memory has ever held — surfaces the right fact, fast. ### Safety — Cross-app capability The pieces that say no on your behalf — so a fast agent never becomes a destructive one. - **Permissions** [shipping]: Per-tool approval rules with wildcard allow/deny so risky actions always pause for you. - **Diff Reviewer** [shipping]: Queues every file write for inspection before it lands — accept, reject or rewrite the patch. - **Sandbox** [shipping]: Restricts which files and domains an agent may touch, even when it is told to do more. - **Verifier** [beta]: Cross-checks an action against your stated intent before money is spent or content is sent. ## Orchestrator The askFinz Orchestrator coordinates work across agents. It classifies intent, plans steps, routes to specialists, executes in parallel, reviews quality, and integrates memory — all without manual configuration. - **Intent Classification**: The Thinker agent reads your prompt and classifies intent, complexity, and required capabilities before routing. - **Multi-Step Planning**: The Planner breaks complex tasks into ordered steps, each tagged with the specialist agent needed. - **Dynamic Routing**: The Router matches each step to the best-fit agent based on capabilities, current load, and reasoning depth required. - **Parallel Execution**: Independent steps run in parallel. The Executor coordinates timing and merges results when dependencies resolve. - **Quality Review**: The Reflector checks finished work against the original brief and requests retries when quality falls short. - **Memory Integration**: The Ingestor pulls relevant context from prior conversations, uploaded files, and saved work before execution. ## Protocols Full details: https://askfinz.com/protocols The askFinz Orchestrator coordinates work across agents using open protocols for agent interoperability. External agents and tools can call askFinz and vice versa. **A2A (Agent-to-Agent)** [Shipping] Agents communicate directly with each other to coordinate complex tasks. The askFinz Orchestrator routes work between specialized agents using structured messages. Use: Internal agent coordination, sub-agent spawning, parallel task execution **MCP (Model Context Protocol)** [Shipping] Anthropic's open standard for connecting AI systems to external data sources and tools. askFinz agents can call MCP servers you configure. Use: External tool integration, custom data sources, third-party services **ACP (Agent Communication Protocol)** [Shipping] IBM's open protocol for structured agent communication and interoperability across different AI systems. Use: Cross-vendor agent communication, enterprise AI interoperability **A2P (Agent-to-Person)** [Soon] Agents pause for human input when needed. Permission requests, confirmations, and clarifications flow through this protocol. Use: Permission requests, CAPTCHA pauses, decision points, review gates **A2UI (Agent-to-UI)** [Soon] Agents stream structured updates to the interface. Progress indicators, intermediate results, and tool calls render in real-time. Use: Live progress streaming, step-by-step visibility, result rendering ## Models Full details: https://askfinz.com/models **Cloud routing (10 providers):** OpenAI, Gemini, Mistral, Llama, Qwen, DeepSeek, Moonshot, NVIDIA NIM, Z.ai, Google Cloud. The router picks the best model per task automatically. Manual override is always available. **On-device models (browser extension):** 380+ open-weight models via WebLLM/MLC. Runs entirely in the browser — no data leaves the device. Available in Chrome and Edge. ## Pricing Full pricing: https://askfinz.com/pricing **Browser Extension & Desktop App** — $8.19/mo (annual: $89.54/yr). No token caps, no usage limits, no restrictions. 380+ AI models. Separate from cloud workspace plans. Cloud workspace plans: - Free: $0 — basic access. - Student: $10/mo — full workspace access at student pricing. - Starter: $15/mo — full workspace + agents + citations. - Pro: $49/mo — higher limits, priority routing, advanced agents. - Business: $149/mo — team features, shared workspace, admin controls. - Enterprise: custom — dedicated infrastructure, SAML SSO, audit logs, askFinz OS access. ### Pricing FAQ **Q: Is annual billing cheaper?** A: Yes — every paid plan is priced lower when you pay yearly instead of twelve monthly payments. You'll see the annual figure on each plan at checkout. **Q: Are there any egress or download fees?** A: No. Downloading your files from askFinz is always free — no egress charges, ever. We built on a provider partnership that makes outbound delivery cost us nothing, so we pass that directly to you. **Q: Can I bring my own keys?** A: Yes. askFinz routes to every major model out of the box, and you can plug in your own provider API keys whenever you'd rather run on your own account. No lock-in — export your data any time. **Q: What does Enterprise add?** A: SAML SSO, audit logs, an isolated data perimeter, dedicated compute, askFinz OS device management and self-host options — shaped to your organisation. It's custom-priced; talk to us. ## Solutions Full details: https://askfinz.com/solutions Industry-specific bundles that combine askFinz workspaces around a real workflow. ### Wealth & finance — https://askfinz.com/solutions/wealth For analysts, advisors and operators of capital — research notebooks, multi-source news, semantic search and KPI dashboards under one login. Key workspaces: Research, News, Finance, Data, Chat, Search. ### Healthcare — https://askfinz.com/solutions/healthcare For medical professionals — literature review, clinical note drafting, drug-interaction lookup and patient-facing content generation. Key workspaces: Research, Chat, Docs, Knowledge, Search. ### Education — https://askfinz.com/solutions/education For students and educators — essay assistance, citation management, quiz generation, course content creation and reading comprehension. Key workspaces: Research, Chat, Docs, Edu, Knowledge, Create. ### Research — https://askfinz.com/solutions/research For academic and professional researchers — deep literature search, source matrix, citation network analysis and long-form synthesis. Key workspaces: Research, Chat, Docs, Search, Knowledge. ### Operations — https://askfinz.com/solutions/operations For business operations teams — workflow automation, data analysis, report generation and cross-tool integration. Key workspaces: Workflow, Data, Dash, Chat, Search, Knowledge. ## Use cases Index: https://askfinz.com/for ### AI for equity research — https://askfinz.com/for/equity-research Build a defensible equity research note in an afternoon — pull 10-K passages, earnings calls and news into one workspace where every figure cites its source. - Pull the read together: Open a notebook per name; cite 10-K passages, the recent call and your own prior notes — each claim next to its source. - Ground it in current news: Sweep deduped, multi-source news clusters on the names you cover so a single story doesn't read four ways. - Search across everything you've filed: Semantic search over the filings, transcripts and notes you've already collected — find the passage, not just the document. ### AI for due diligence — https://askfinz.com/for/due-diligence Run a consistent diligence pass over every target — the same rubric, the same source breadth, the same length each time, every finding traceable. - Apply one rubric to every target: Branch the same diligence question set per company so each gets the same depth — no target gets the thin treatment. - Read the document room: Upload the data-room files and search across them semantically; pull the clause or figure, not the 200-page PDF. - Check the public record: Sweep deduped news clusters for litigation, leadership churn and the stories that don't make the management deck. ### AI for market research — https://askfinz.com/for/market-research Turn a market question into a sourced brief — reports, filings and multi-source news in one searchable workspace, every claim traced to its origin. - Frame the question as a notebook: Open a notebook per market or segment; branch sub-threads for sizing, players and trends so the structure mirrors the brief. - Synthesise the reading: Pull the reports and articles into one place and let the workspace draft the synthesis — agreement on top, disagreement surfaced underneath. - Track the live signal: Deduped, multi-source news clusters keep the brief current between updates instead of going stale the week after you write it. ### AI for competitive analysis — https://askfinz.com/for/competitive-analysis Track competitors in one workspace — filings, releases and news synthesised into a living battlecard, every claim linked to the source behind it. - A thread per competitor: Branch a notebook thread for each rival so positioning, pricing moves and launches accumulate in one place over time. - Catch the moves early: Deduped, multi-source news clusters surface a competitor's announcement once — not four near-identical times — the day it lands. - Synthesise into a battlecard: Let the workspace draft the comparison — where they're ahead, where they're exposed — with each line linked to its source. ### AI for financial analysts — https://askfinz.com/for/financial-analysts One workspace for the analyst's day — morning briefing, citation-backed notes, watchlist news and a searchable record of everything you've read. - Morning briefing: Pull the day's signal across feeds, deduped and clustered by holding or sector — the read, not the noise. - Citation-backed notes: Draft a note where every number links back to the page it came from, in your house template. - Ask across models: Switch between AI models in one thread for the question at hand — bring files, keep the history. ### AI for consultants — https://askfinz.com/for/consultants Research, synthesise and write the deliverable in one workspace — turn a client question into a sourced, defensible brief without the four-tool scramble. - Scope the question: Open a notebook per engagement; branch threads for the market, the players and the recommendation so structure mirrors the deck. - Synthesise the inputs: Pull reports, interviews and articles into one place and draft the synthesis with sources attached. - Draft across models: Switch AI models mid-thread for framing, rewriting or stress-testing the argument — keep the whole history. ### AI for literature reviews — https://askfinz.com/for/literature-review Run a literature review in one workspace — synthesise papers into a sourced summary, search everything you have read, keep every claim cited. - Organise the corpus: Bring the papers into one notebook; branch threads by question or theme so the structure matches the review. - Synthesise with citations: Draft a synthesis that puts agreement on top and surfaces where the literature conflicts — each claim linked to its paper. - Search across the reading: Semantic search over the whole corpus: find the finding, the method or the quote without re-skimming every PDF. ### AI coding assistant for developers — https://askfinz.com/for/developers Code with AI across the web IDE, your browser and the desktop app — one assistant, your files and history, available wherever you work. - Code in a real IDE: A VS Code-style web IDE with AI built in — read, edit and run across your project, not just a chat box pasting snippets. - Bring AI into the browser: The extension puts the assistant on the pages you already work on, so help is one keystroke away without a context switch. - Work natively on the desktop: The desktop app brings the IDE and assistant into a native window, sharing the same session as web. ### AI for clinical research — https://askfinz.com/for/clinical-research Search registered clinical trials by condition or phase, read them beside the published literature, and file a sourced summary traced to the record. - Pull the registered trial record: Search registered studies by condition, intervention or population and bring the record — sponsor, phase, status — into a notebook, not just a summary. - Read it beside the literature: Pull the papers written about a trial into the same notebook, so its registered design and its published results sit next to each other. - Search across everything you've collected: Semantic search over trial records, papers and your own notes — find the detail without re-opening every record. ### AI for legal research — https://askfinz.com/for/legal-research Search judgments and legislation by the point of law, not just the case name, and draft a memo where every proposition carries its formal citation. - Search by the point of law: Find judgments across jurisdictions that turned on the same issue, without knowing the case name going in. - Read legislation and judgments together: Pull the statute and the cases that interpreted it into one notebook, so the provision and its case history sit side by side. - Keep the formal citation attached: Every case and section carries its official reference, so a memo cites correctly instead of paraphrasing away the source. ### AI for patent search — https://askfinz.com/for/patent-search Search patents by what an invention does across offices worldwide, read prior art beside the literature, and keep a documented trail for every filing. - Search by function, not phrasing: Describe what an invention does and find matching filings across offices, even when they use different terminology than you would. - See the landscape: Pull filings from multiple offices into one notebook, so who's filing where and how a field has moved becomes visible rather than assumed. - Read patents beside the papers: Prior art and the academic literature behind it turn up in the same search, so a prior-art pass and a lit review draw from one index. ### AI for compliance monitoring — https://askfinz.com/for/compliance-monitoring Track regulatory filings, enforcement actions and rule changes in one workspace — deduped news, searchable guidance, and a citation on every finding you file. - Watch the regulatory feed: Deduped, multi-source news clusters surface enforcement actions and rule changes once, not four times, the day they land. - Track a name or a rule: Keep a standing notebook per entity or regulation, so new filings and coverage accumulate over time instead of starting from zero each review. - Search the record: Semantic search across filings, guidance and the news you've collected — pull the clause or the line, not the whole document. ### AI for procurement research — https://askfinz.com/for/procurement-research Search public contract notices by what you supply, read the full notice instead of a summary, and track a buyer or category as new notices are published. - Find the notices that match: Describe what you supply and search contract notices by that, not by remembering the exact procurement category. - Read the full notice, not a summary: Pull the published notice itself into a notebook, so the detail that decides whether to bid isn't lost in a snippet. - Track a market over time: Keep a standing notebook on a buyer or a category, so new notices accumulate in one place instead of a fresh search each week. ### AI for product research — https://askfinz.com/for/product-research Turn competitor releases, reviews and market coverage into a sourced synthesis, then carry the finding straight into a ticket on your team's board. - Synthesise the reading: Pull competitor releases, reviews and market reports into a notebook and let the workspace draft a synthesis with sources attached. - Search what you've already gathered: Semantic search over past research so a decision made two quarters ago is one query away instead of a forgotten doc. - Track the market signal: Sweep the web for what's actually being said about a category, not just the three articles someone happened to send around. ### AI for content research — https://askfinz.com/for/content-research Research a story before you write it — sweep deduped coverage, pull the supporting data, and draft with a citation on every claim an editor can check. - Frame the piece as a notebook: Open a notebook per story or campaign; branch threads for angle, data and sourcing. - Sweep the current coverage: Deduped, multi-source news clusters show what's already been said, so the piece adds something instead of repeating the wire. - Pull the supporting data: Search across reports and articles you've gathered and let the workspace draft the synthesis with citations attached. ### AI for teaching prep — https://askfinz.com/for/teaching-prep Turn your own lecture material into quizzes, summaries and flashcards scoped to this week's unit, and research a current example with its source attached. - Turn material into study tools: Upload your lecture slides and readings and generate summaries, quizzes and flashcards from your own content, not a generic bank. - Scope the tools to this week's unit: Mark the slide ranges for a unit and every quiz and summary stays on that unit instead of the whole course. - Research the gaps: Open a research notebook to pull in a supporting reference or a current example, with the source attached so you can defend it in class. ### AI for student research — https://askfinz.com/for/student-research Read your course material with per-file summaries, research beyond the reading list, and draft with a citation on every claim ready for your bibliography. - Study the source material properly: Bring in your course readings and lecture material and use the per-file summaries and key concepts to understand a topic before you write about it. - Research the assignment: Open a notebook, pull in papers and articles beyond your course pack, and draft a synthesis that surfaces where sources agree and disagree. - Keep every claim linked to a citation: Each point in the draft carries a reference back to its source, so a bibliography is built as you go, not reconstructed the night before it's due. ### AI for technical documentation — https://askfinz.com/for/technical-documentation Draft documentation grounded in what your code actually does, check how similar problems have been answered elsewhere, and keep every revision versioned. - Draft from the actual code: Ask the assistant about your codebase in the IDE and turn its answer into a first draft of the doc, grounded in what the code does today. - Check how it's already been answered: Search across public Q&A threads for how others have solved the same problem, so a doc addresses the question people actually ask. - Research the edge cases: Open a notebook to pull in the relevant release notes or specs a doc needs to reference, with each claim linked to its source. ### AI for accountants: reconciliation and reporting — https://askfinz.com/for/accountants A global markets terminal with live prices, company financials, AI forecasts, and alerts for easy market monitoring. - Monitor market trends: Track real-time stock prices and AI-generated forecasts to adjust investment strategies. - Retrieve financial data: Drop a file, ask a question, get a chart. - Create a dashboard: Connect your data, drag fields onto a canvas, build charts and share them. ### AI for founders: research, pitch and diligence — https://askfinz.com/for/founders Track your portfolio, forecast prices, and manage projects with real-time insights — all in one place. - Manage billing and plans: Edit seats and upgrade plans to manage costs and access - Open a watchlist: Add stocks, ETFs, or crypto to track market movements - Create a sprint: Add a new sprint to the project board, set a start date, and assign tasks to team members. ### AI for traders: filings, news and market context — https://askfinz.com/for/traders A global markets terminal with live prices, AI forecasts, and portfolio tools. - Access live prices and research: Use the terminal to view live stock, ETF, crypto, index, and option prices, along with AI forecasts and research in plain English. - Create a dashboard: Connect data, drag fields onto canvas, build charts, share with team - Listen to the briefing: Hear the day's news in your preferred voice, with stories clustered by importance. ### AI for students: research, revision and citations — https://askfinz.com/for/students Turn your course into AI study tools, a lockdown exam simulator, and a knowledge bank. - Learn a course: Bring in your real course material and Learn turns it into AI study tools, a lockdown exam simulator, a knowledge bank and honest progress analytics — grounded in your own lectures, explained in plain English. - Branch research paths: Explore multiple angles on the same question, merge the best findings later - Read and cite: Open a notebook per name and cite the filing passage, the latest call and your prior notes, each claim beside its source. ### AI for lawyers: case law, contracts and drafting — https://askfinz.com/for/lawyers Draft contracts and briefs in hours, not days — with every clause explained and every risk highlighted. - Study a case law: Open a notebook and cite the relevant filing passage, the latest call, and your prior notes. - Branch research paths: Explore multiple angles on the same question, merge the best findings later - Read the manual: Open the Docs workspace and follow the instructions to understand how to use askFinz effectively. ## Guides (70) **Guides** — https://askfinz.com/guides Practical guides to using AI for real work — by workspace, by industry, and by use case. ### Crawling vs indexing vs scraping — https://askfinz.com/guides/crawling-vs-indexing-vs-scraping Crawling, indexing and scraping get used as synonyms, but they're three different jobs. A plain-English breakdown of what each one actually does. "We crawled the site." "We scraped the data." "It's in the index now." In casual conversation these three phrases get swapped for each other constantly, and most of the time nobody notices, because the words are close enough that the sentence still makes sense. But they describe three different jobs, done by three different pieces of software, and mixing them up is the reason a lot of "why isn't my data showing up" confusion happens in the first place. Here is the plain version, in the order the work actually happens. Full article: https://askfinz.com/guides/crawling-vs-indexing-vs-scraping ### How to get your site indexed by AI search — https://askfinz.com/guides/get-my-site-indexed-by-ai Waiting to be discovered isn't the only option. How to get your site read, indexed and answerable by AI search — and how to keep control of it. If you run a website, "will AI search engines find me" used to be a question you couldn't do much about — you published, and you waited to be discovered whenever a crawler happened to reach you. That's still partly true. But it's worth understanding both halves of the picture: what happens automatically, and what you can actually do to speed it up or take more control over how your site is read. Full article: https://askfinz.com/guides/get-my-site-indexed-by-ai ### Why a headless browser gets a 403 — https://askfinz.com/guides/headless-browsers-get-blocked Same machine, same cookies, wildly different result. Why headless Chromium gets refused where a real browser sails through — and what that means. Here's a scenario that trips up a lot of engineers the first time they hit it: you write a script using headless Chromium, point it at a page you can open fine in your normal browser, and it comes back with a 403. Same URL. Same cookies, if you copy them over. Sometimes even the same IP address. And yet one gets the page and the other gets refused outright. Full article: https://askfinz.com/guides/headless-browsers-get-blocked ### How a search index is actually built — https://askfinz.com/guides/how-a-search-index-is-built From a URL to an instant answer — a start-to-finish, plain-English walk through how a search index actually gets built and kept current. Typing a question into a search box and getting an answer back in a fraction of a second feels instantaneous, and that's exactly the point — none of the real work happens at query time. It happens beforehand, continuously, in a pipeline that turns the open web into something that can be searched instantly. Here's what that pipeline actually looks like, stage by stage. Full article: https://askfinz.com/guides/how-a-search-index-is-built ### How AI search actually finds an answer — https://askfinz.com/guides/how-ai-search-finds-answers From your question to a sourced answer — how AI search bridges a live index and a language model to answer in words instead of ten blue links. Type a question into a traditional search engine and you get a page of links, ranked by relevance, and it's on you to open a few, read them, and work out the answer yourself. Type the same question into an AI search engine and you get an actual answer, in a sentence or two, with sources attached. The difference feels like magic, but the mechanism underneath it is well understood, and it's really just two established ideas working together in sequence: a search index, and a language model. Full article: https://askfinz.com/guides/how-ai-search-finds-answers ### What web data actually costs — https://askfinz.com/guides/how-much-does-web-data-cost Every AI product needs web data from somewhere. The real cost difference isn't the sticker price — it's whether you rent an index or own one. Every AI product that answers a question about the current world needs web data from somewhere. Almost none of them read the web themselves — building and running that kind of infrastructure is a serious undertaking, so the overwhelming majority buy access to someone else's search results through an API and pass the cost (and the constraints) straight through to whatever they're building. Full article: https://askfinz.com/guides/how-much-does-web-data-cost ### Why most search can't read a PDF properly — https://askfinz.com/guides/indexing-pdfs-and-documents Slide decks, scans and reports hold some of the most useful information on the web — and most search engines link to them without reading a word. Try searching for a specific fact from a research report, a regulatory filing, or a company's investor deck, and you'll notice something odd: search engines will often find the document — they know it exists, they can show you the filename and the link — but they can't tell you what's actually on page 14. They found it. They didn't read it. This is one of the most underserved gaps in how search generally works, and it matters more than it looks like it should, because a huge share of genuinely useful information lives in exactly this kind of file rather than in an ordinary web page. Full article: https://askfinz.com/guides/indexing-pdfs-and-documents ### Real-time vs scheduled indexing — https://askfinz.com/guides/real-time-vs-scheduled-indexing Days to weeks behind, or searchable the moment it's read — the difference between scheduled crawling and real-time indexing, explained plainly. Ask most search systems how current their results are and you'll get a vague, reassuring answer. Ask more precisely — "if this page changed an hour ago, does your index know?" — and the honest answer, for a lot of systems, is no. Not because anyone is hiding anything, but because of how indexing has traditionally been built: on a schedule, not continuously. Full article: https://askfinz.com/guides/real-time-vs-scheduled-indexing ### How robots.txt works for AI crawlers — https://askfinz.com/guides/robots-txt-and-ai-crawlers What robots.txt actually controls, how AI crawlers are supposed to read it, and how to check whether yours is doing what you think it is. A rising number of webmasters are asking a version of the same question: with AI crawlers now reading the web to build search indexes and train models, does my old `robots.txt` file still do what I think it does — and does it even cover the new crawlers showing up in my logs? The honest answer is: mostly yes, with some details worth getting right. Full article: https://askfinz.com/guides/robots-txt-and-ai-crawlers ### What is a vector index? — https://askfinz.com/guides/what-is-a-vector-index How a vector index lets a search system match ideas instead of exact words — a plain-English explanation of "searching by meaning." Search a keyword-based system for "how to stop feeling anxious before a talk" and it will look for pages containing those specific words. Miss the exact phrasing — the source you actually need says "manage nerves before public speaking" — and a keyword match can walk right past it, even though it's clearly the answer. A vector index exists to fix exactly this problem: it lets a system match on what something means, not on which words happen to appear. Full article: https://askfinz.com/guides/what-is-a-vector-index ### What is a web crawler? — https://askfinz.com/guides/what-is-a-web-crawler What a web crawler actually does, how it decides where to go next, and how a well-behaved one is supposed to treat the sites it visits. Every search engine, every AI system that reads the live web, and every index of any real size starts with the same piece of software: a crawler. It's one of the oldest ideas in how the internet gets organised, and also one of the most misunderstood — mostly because "crawling" gets used loosely to mean almost any kind of automated visit to a website, when it actually describes something specific. Full article: https://askfinz.com/guides/what-is-a-web-crawler ### Who owns the index behind your AI? — https://askfinz.com/guides/who-owns-the-index-behind-your-ai Most AI search features call a rented search index. Here's how to tell who owns theirs, why it sets their price, and what happens when it gets pulled. Ask an AI product where its web search actually comes from, and most of the time the honest answer is: not from them. The chatbot, the agent, the research tool — whatever sits on top — is usually a thin, well-designed layer over a search index someone else built. That's not a criticism; building and running a web-scale index is one of the harder infrastructure problems in software, and renting access to one is a completely reasonable way to ship a product. Full article: https://askfinz.com/guides/who-owns-the-index-behind-your-ai ### Why web scraping breaks (and keeps breaking) — https://askfinz.com/guides/why-web-scraping-breaks Selectors move, sites redesign, blocks appear overnight. Why scraped data pipelines fail so often — and what actually keeps working instead. If you've ever maintained a scraper, you know the pattern: it works fine for weeks, then one morning it returns nothing, or worse, returns garbage that looks fine until someone notices the numbers are wrong. Nothing about your code changed. The website did. This isn't bad luck or bad engineering. It's the structural problem with scraping as an approach — you're building against a target that has no obligation to stay still. Full article: https://askfinz.com/guides/why-web-scraping-breaks ### Agent-to-agent (A2A), explained — https://askfinz.com/guides/agent-to-agent-a2a-explained Agent-to-agent (A2A) lets AI agents hand off tasks to each other — enabling more complex, multi-step work than any single agent can handle on its own. A single AI assistant can do a lot. But some work is genuinely too large, too varied, or too parallel for one agent to handle end-to-end. Agent-to-agent (A2A) protocols define how AI agents can hand tasks to each other — breaking complex work into pieces, routing each piece to the agent best suited to handle it, and assembling the results. Understanding A2A helps clarify what is actually possible when AI systems are described as "agentic." Full article: https://askfinz.com/guides/agent-to-agent-a2a-explained ### AI agents vs. chatbots — the difference — https://askfinz.com/guides/ai-agents-vs-chatbots AI agents vs chatbots explained simply: chatbots respond to questions; agents take actions and work through multi-step tasks on your behalf. If you've heard "AI agents" mentioned alongside chatbots and wondered what the actual difference is, you're not alone. The two terms get used interchangeably in a lot of marketing copy, but they describe meaningfully different things — and the difference matters when you're thinking about what AI can do for your work. The short version: a chatbot responds. An agent acts. Full article: https://askfinz.com/guides/ai-agents-vs-chatbots ### The askFinz browser extension — https://askfinz.com/guides/ai-browser-extension The askFinz AI browser extension puts a full AI side panel on any webpage — research, summarise, and act without leaving the tab you're already on. Most AI tools make you leave what you're doing. You copy a block of text, switch tabs, paste it in, get an answer, then switch back. The askFinz [browser extension](/extension) skips all of that — the AI panel lives alongside the page you're already on, so you never lose your place.
Full article: https://askfinz.com/guides/ai-browser-extension ### AI chat across every major model, in one place — https://askfinz.com/guides/ai-chat-every-model Stop juggling ChatGPT, Claude, and Gemini in separate tabs. askFinz gives you multi-model AI chat in one place — same prompt, every model, no switching. There are more capable AI models available today than at any point in history. There are also more logins, more browser tabs, and more moments where you copy-paste a prompt from one window into another hoping the answer is better this time. askFinz closes that loop: one place to talk to every major model, compare what they give you, and keep your conversation history in one thread. Full article: https://askfinz.com/guides/ai-chat-every-model ### An AI coding workspace for whole projects — https://askfinz.com/guides/ai-coding-workspace An AI coding assistant that works across your whole project — not just the line you're typing. Write, review, explain and iterate without switching tools. AI autocomplete that finishes your current line is useful. An AI that understands the file you are in is more useful. An AI that understands the whole project — the structure, the dependencies, the decisions made three months ago in a file you have not opened today — is something else entirely. That is what askFinz Code is built around.
Full article: https://askfinz.com/guides/ai-coding-workspace ### Build dashboards with AI — no SQL — https://askfinz.com/guides/ai-dashboard-builder An AI dashboard builder that turns plain-language questions into charts and live dashboards — so your data tells its story without a BI analyst in the way. Most organisations are sitting on data they cannot easily see. The numbers are in a database somewhere, or a spreadsheet someone maintains, or a system that has a reporting tab nobody fully understands. Getting from "I want to know X" to a chart you can act on typically requires someone who knows SQL, a BI tool that takes days to configure, or a data analyst whose queue is already full. An AI dashboard builder is coming to askFinz. The goal is simple: ask the question in plain language and get the chart — no query language, no BI license, no waiting. Full article: https://askfinz.com/guides/ai-dashboard-builder ### Turn your docs into a readable AI manual — https://askfinz.com/guides/ai-documentation How an AI documentation tool transforms scattered internal docs into something anyone can query — so your team stops guessing and starts finding. Most teams have more documentation than they realise. What they do not have is documentation that is easy to use. The onboarding guide lives in one folder, the process notes in another, the updated version of the policy somewhere nobody remembers. The information exists — it is just not *queryable*. An AI documentation tool changes that: instead of searching through files, you ask a question and the answer comes back from the documents themselves. Full article: https://askfinz.com/guides/ai-documentation ### AI for creative & media teams — https://askfinz.com/guides/ai-for-creative-and-media-teams How creative and media teams use AI for creators to move from brief to publish faster — without losing the voice, the quality, or the creative control. Creative work has two phases that feel completely different but are rarely separated cleanly: the part where ideas form, and the part where ideas become things. The first phase is irreducibly human. The second — research, drafting, iteration, formatting, scheduling — contains a lot of work that does not require creativity to execute. AI's place in creative and media teams is in that second phase: compressing the production cycle so more time goes to the first. Full article: https://askfinz.com/guides/ai-for-creative-and-media-teams ### AI for education & learning teams — https://askfinz.com/guides/ai-for-education How education teams use AI for education to build courses, support learners, and cut the prep work that crowds out real teaching. Teaching is one of the most preparation-heavy professions there is. For every hour in front of students, there are hours behind the scenes: planning lessons, writing materials, researching topics, giving feedback, answering the same question seventeen different ways for seventeen different learners. AI does not replace any of that. It does mean that more of it can happen without the teacher carrying all the weight alone. Full article: https://askfinz.com/guides/ai-for-education ### AI in healthcare, used responsibly — https://askfinz.com/guides/ai-for-healthcare How healthcare teams use AI for research, documentation, and patient-facing work — with the human always in control and every source visible. Healthcare work demands more than speed. Every note, every summary, every piece of research exists in a context where the wrong answer has real consequences. The question is not whether AI has a place in clinical and healthcare settings — it already does — but whether it is used in a way that keeps the professional in control, the reasoning visible, and the patient's interests protected. Full article: https://askfinz.com/guides/ai-for-healthcare ### AI for legal teams — https://askfinz.com/guides/ai-for-legal-teams How legal teams use AI for legal work — research, drafting, and document review — with the lawyer always in control and every source traceable. Legal work carries a particular kind of professional responsibility. An answer that is wrong, incomplete, or untraceable is not just unhelpful — it can cause harm. The case for AI in legal settings is therefore more careful than in most: the tool must earn trust through transparency, not undermine it through convenience. Used correctly, AI can give legal professionals more time for the work that actually requires their expertise. Used carelessly, it creates exactly the risks it is supposed to reduce. Full article: https://askfinz.com/guides/ai-for-legal-teams ### AI for markets and portfolios — https://askfinz.com/guides/ai-for-markets-and-portfolios How an AI finance assistant helps investors and advisors track markets, review portfolio positions, and turn research into decisions — all in one place. Market information is everywhere. The problem is not access — it is *making sense of it in time to act*. By the time you have pulled data from three sources, cross-referenced a position, and drafted a note on what it means, the window has often moved. An AI finance assistant is useful not because it knows more than you do, but because it removes the manual steps between having a question and having an answer worth acting on. Full article: https://askfinz.com/guides/ai-for-markets-and-portfolios ### AI for operations teams — https://askfinz.com/guides/ai-for-operations-teams How operations teams use AI for operations to move faster on decisions, documentation, and cross-team coordination — without more tools to manage. Operations is the connective tissue of every organisation — the function that keeps everything moving, coordinates across teams, and absorbs the work that does not belong anywhere else. It is also, typically, the function most buried in process: tracking, documenting, escalating, reporting, chasing. AI does not change what operations does. It dramatically changes how much of that load requires a human to carry it manually. Full article: https://askfinz.com/guides/ai-for-operations-teams ### AI for research-heavy work — https://askfinz.com/guides/ai-for-research-heavy-work How teams doing deep research use AI for research to move from scattered sources to a cited, defensible answer — without losing the trail. Research-heavy work has a specific frustration: the ratio of time spent finding and organising material to time spent actually thinking about it is badly skewed. A researcher, analyst, or strategist might spend three hours pulling sources together before spending thirty minutes forming an opinion. AI does not replace the opinion — but it can reshape that ratio.
Full article: https://askfinz.com/guides/ai-for-research-heavy-work ### AI for wealth & finance teams — https://askfinz.com/guides/ai-for-wealth-and-finance-teams How advisory, wealth and finance teams use askFinz to research markets, draft client-ready notes, and build dashboards — without juggling ten tools. Finance work lives or dies on two things: getting to a defensible answer quickly, and being able to show your work. Most teams lose hours to neither — they lose them to *switching*: a tab for research, another for the spreadsheet, a third for the chart, a fourth for the memo. askFinz is built to collapse that into one place.
Full article: https://askfinz.com/guides/ai-for-wealth-and-finance-teams ### A second pair of eyes for health questions — https://askfinz.com/guides/ai-health-assistant How an AI health assistant helps you understand medical information, prepare for appointments, and navigate decisions — without replacing your doctor. Health questions are uniquely stressful to research. The information online is abundant but uneven — authoritative articles sit alongside outdated advice, and the search results rarely distinguish between them. You come away with more words but not necessarily more clarity. An AI health assistant is not a replacement for medical care. It is a way to walk into that care better prepared: with clearer questions, a better understanding of the terminology, and a calmer sense of what you are dealing with. Full article: https://askfinz.com/guides/ai-health-assistant ### A creative studio for AI rendering — https://askfinz.com/guides/ai-image-studio How an AI image studio lets individuals and teams generate, iterate, and use visuals without design tools or waiting for someone with design skills. Most work that needs a visual is not design work — it is communication work. A concept that needs illustrating, a presentation that needs a header, a prototype that needs to show how something might look. The people who need these visuals are rarely designers, and the solution is usually one of three things: wait for someone who is, pay for a service, or go without. An AI image studio offers a fourth path: describe what you want and see it rendered. Full article: https://askfinz.com/guides/ai-image-studio ### An AI inbox & calendar assistant — https://askfinz.com/guides/ai-inbox-and-calendar An AI email assistant that reads, prioritises and drafts — so you spend less time processing your inbox and more time on the work that actually matters. The inbox was never supposed to be the job. It is the channel through which the job arrives — requests, decisions, updates, invitations. But for most people, managing the inbox has become a significant part of the working day in its own right: reading, triaging, drafting, chasing, filing. askFinz Mail is built to reduce that overhead, so the time you spend on communication reflects its actual importance rather than the volume of it. Full article: https://askfinz.com/guides/ai-inbox-and-calendar ### Connect every tool into one AI knowledge base — https://askfinz.com/guides/ai-knowledge-base How teams use askFinz as an AI knowledge base to surface the right answer from every document, note, and system — without digging through folders. Most teams are not short on information. They are short on *findable* information. There's a document in one place, a note from last week in another, a decision made in a thread nobody can locate. The knowledge exists — it just isn't connected. An AI knowledge base changes that by giving every team member a single place to ask a question and get an answer drawn from everything the team already knows. Full article: https://askfinz.com/guides/ai-knowledge-base ### Case law and contracts in plain English — https://askfinz.com/guides/ai-legal-assistant How legal teams use an AI legal assistant in askFinz to research case law, review contracts, and produce plain-English summaries — fast and fully sourced. Legal work involves two distinct skills: understanding what the law says, and explaining it clearly to someone who isn't a lawyer. Most of the time cost falls on the first part — reading through case law, cross-referencing statutes, reviewing contract language — before you can do the more valuable part of actually advising someone. askFinz **Legal** is coming to compress that research time, so more of the work stays at the level that actually matters. Full article: https://askfinz.com/guides/ai-legal-assistant ### Go live and build a community — https://askfinz.com/guides/ai-live-streaming How creators use AI live streaming tools in askFinz to broadcast, engage their audience, and manage community channels — all from one place. Going live has never been technically simpler. What still takes time is everything around the stream: writing the description, fielding chat, keeping the community engaged between broadcasts, and figuring out what actually landed with your audience. Most creators manage that across a handful of disconnected tools — a streaming platform, a community server, a notes app, a scheduler. askFinz **Stream** is coming to bring it together. Full article: https://askfinz.com/guides/ai-live-streaming ### Your day's news, summarised by AI — https://askfinz.com/guides/ai-news-briefing An AI news summary that reads the noise so you don't have to — filtered by topic, with verifiable sources and no algorithm deciding what matters to you. The news does not get shorter. If anything, the amount of content competing for your attention at the start of each day increases, while the amount of time you have to process it does not. Most people respond by giving up on reading the news properly, or by spending more time than they should trying to extract the ten things that actually matter from the hundred that do not. askFinz News is a third option. Full article: https://askfinz.com/guides/ai-news-briefing ### AI-organised file storage — https://askfinz.com/guides/ai-organised-file-storage AI file management that keeps your storage organised without you doing the organising — find anything fast, from anywhere, with the context you need. The problem with file storage is not storage. It is retrieval. Saving a file takes seconds. Finding it six weeks later, when you remember roughly what it was about but not what you called it or where you put it, can take considerably longer. askFinz Storage is built around the assumption that a file is only useful if you can find it — and that finding it should not require perfect memory or rigid folder discipline. Full article: https://askfinz.com/guides/ai-organised-file-storage ### Every account, one place to see your money — https://askfinz.com/guides/ai-personal-finance How individuals use AI personal finance tools in askFinz to track accounts, understand spending, and plan ahead — without logging into six separate apps. Most people manage their money across more places than they realise: a current account here, a savings pot there, a credit card with a different bank, a pension somewhere else entirely. Each one has its own app, its own login, its own view of the world. The result is that you almost never see the whole picture at once. askFinz **Bank** is coming to change that — one place where every account is visible and your finances start to make sense together. Full article: https://askfinz.com/guides/ai-personal-finance ### A project tool that knows the rest of your work — https://askfinz.com/guides/ai-project-management AI project management that links tasks to the research and conversations behind them — so nothing important gets lost in a tool your team forgets to check. Most project tools have the same blind spot: they track *what* needs doing, but none of the *why* behind it. The decision thread is in Slack. The research is in a doc someone shared last month. The context that makes a task make sense is somewhere else — and over time, teams spend as much energy re-finding that context as they do doing the actual work. [askFinz Projects](/apps/project) is different because it shares a workspace with everything else. The task knows about the conversation that created it. The brief is right there, not linked from a third-party tool. Full article: https://askfinz.com/guides/ai-project-management ### Property listings, distilled by AI — https://askfinz.com/guides/ai-real-estate How buyers and agents use AI real estate tools in askFinz to research listings, compare neighbourhoods, and move from first question to confident offer. Finding a property is easy. Making sense of the market around it — schools, comparable sales, planning history, neighbourhood trends — is where the real work begins. Most buyers and agents cobble together five or six sources and then try to hold it all in their head at once. askFinz's **Estate** workspace is coming to consolidate that into one place.
Full article: https://askfinz.com/guides/ai-real-estate ### AI research that cites its sources — https://askfinz.com/guides/ai-research-that-cites-sources An AI research tool that doesn't just give you an answer — it shows where the answer came from, so you can trust it, share it, and defend it. The hardest problem with AI-generated research is not the quality of the answer — it is the silence about where the answer came from. You get a confident summary, a clean paragraph, a tidy list of conclusions. What you do not get is a way to check any of it. askFinz Research is built around a different assumption: an answer is only useful if you can verify it.
Full article: https://askfinz.com/guides/ai-research-that-cites-sources ### An AI search engine for people, agents and LLMs — https://askfinz.com/guides/ai-search-engine An AI search engine that understands questions, not just keywords — built for people doing real work and for the agents and LLMs working alongside them. Search was designed for a world where you knew how to phrase the right keyword. It works well if you already know roughly what you are looking for and how it is likely to be described. It works less well for the kind of questions that actually arise in the middle of complex work — questions that are half-formed, context-dependent, or genuinely open-ended. askFinz Search is designed for those questions. Full article: https://askfinz.com/guides/ai-search-engine ### Multi-account social posting & scheduling — https://askfinz.com/guides/ai-social-media-posting How teams and creators use AI social media tools in askFinz to draft, schedule, and publish across multiple accounts — without toggling between platforms. Posting consistently on social media sounds simple until you're actually doing it. Writing for multiple platforms means adapting tone and format for each one. Managing more than one account or brand means tracking what went out where and when. Scheduling ahead means maintaining a calendar across tools that don't share context. Most teams end up with a patchwork of apps that technically work but slow everything down. askFinz **Socials** is coming to replace that patchwork with one place. Full article: https://askfinz.com/guides/ai-social-media-posting ### A storefront native to your AI platform — https://askfinz.com/guides/ai-storefront How creators and teams use an AI storefront in askFinz to sell products, manage orders, and handle customer questions — without a separate e-commerce tool. Most storefronts are built for a separate context: you make the thing somewhere, market it somewhere else, sell it on a third platform, and handle support on a fourth. Every handoff is a small tax on your time. askFinz **Shop** is coming to put the selling surface inside the workspace where the rest of your work already happens. Full article: https://askfinz.com/guides/ai-storefront ### Plan and book a whole trip in a paragraph — https://askfinz.com/guides/ai-travel-planner An AI travel planner that turns a single prompt into booked flights, stays, and activities — without juggling airline tabs, hotel sites, or itinerary docs. Planning a trip is one of those tasks that looks simple from the outside — you pick where you're going, find somewhere to stay, book a flight — and then you open the browser and ten tabs turn into twenty. Prices on one site don't include the fees shown on another. The hotel you liked sold out by the time you checked back. The itinerary you were building in a Google doc drifts away from the bookings you actually made. Full article: https://askfinz.com/guides/ai-travel-planner ### An AI tutor that follows your pace and progress — https://askfinz.com/guides/ai-tutor How an AI tutor adapts to how you learn, remembers where you left off, and helps you go deeper on any subject — at any pace, on any device. The best tutoring is responsive. It meets you where you are, adjusts when something is not landing, and moves at a pace that works for you rather than for a class of thirty. Most people have never experienced that kind of learning because access to it has always been expensive, scarce, or both. An AI tutor changes the economics without changing the principle: responsive, patient, personalised learning available whenever you want to use it. Full article: https://askfinz.com/guides/ai-tutor ### Drag-and-drop AI workflow automation — https://askfinz.com/guides/ai-workflow-automation AI workflow automation built for non-engineers — connect tools, trigger actions, and route decisions with a visual canvas that ships in beta on askFinz. Most teams have a process that works — it just has too many manual steps in the middle. Someone checks a result and copies it into a form. Someone reads a summary and sends it to the right person. Someone checks whether a threshold was crossed and triggers the next step. These are not complex decisions. They're just repetitive, and the people doing them are too capable to be spending time on them. Full article: https://askfinz.com/guides/ai-workflow-automation ### askFinz Cloud: every AI workspace, one login — https://askfinz.com/guides/askfinz-cloud-workspaces askFinz Cloud gives you every AI tool — research, chat, code, charts, knowledge — under one login, accessible from any browser on any device. The default way to use AI at work is to have several accounts at several providers, each one good at one thing, each one needing its own login. That adds up quickly to more switching than working. askFinz Cloud puts every workspace on a single [platform](/platform) under one login, so you can move between tools the way you move between rooms in the same building — not between buildings.
Full article: https://askfinz.com/guides/askfinz-cloud-workspaces ### askFinz Desktop: your AI workspace — https://askfinz.com/guides/askfinz-desktop-app The askFinz AI desktop app brings your full workspace — browser, IDE, storage and AI — into a single native app that runs independently of your browser. A browser tab is a fragile place to do serious work. It competes with every other open tab, it disappears if the window closes, and it can't interact with the files and tools sitting on your machine. askFinz [Desktop](/desktop) takes the full workspace out of the browser and puts it on your computer as a proper application — persistent, focused, and connected to what's already on your device.
Full article: https://askfinz.com/guides/askfinz-desktop-app ### askFinz OS: an operating system built around AI — https://askfinz.com/guides/askfinz-os askFinz OS is an emerging AI operating system where AI assistance is part of the environment itself — not an add-on to an existing desktop. Every current approach to AI on a computer follows the same pattern: you have an operating system, and then you have an AI tool installed on top of it. The AI is a guest in an environment not built for it. askFinz [OS](/os) is an early exploration of a different question — what does an operating system look like when AI is part of the environment from the start, not an afterthought? Full article: https://askfinz.com/guides/askfinz-os ### Automate the repetitive parts of your week — https://askfinz.com/guides/automate-repetitive-work Automate work with AI by setting up workflows that handle the recurring, predictable tasks so your time goes to the work that actually needs you. Most knowledge workers can name at least three or four things they do every week that follow exactly the same pattern. The weekly summary. The status update pulled from multiple sources. The report formatted, checked, and sent to the same people. These tasks aren't difficult — they're just reliably time-consuming, and they tend to land at the worst moments. Automation isn't about replacing judgment. It's about not spending your attention on the parts of work that don't require it. Full article: https://askfinz.com/guides/automate-repetitive-work ### Choosing AI tools for your team — https://askfinz.com/guides/choosing-ai-tools-for-your-team A practical guide to evaluating the best AI tools for teams — what questions to ask, what traps to avoid, and how to tell capability from marketing. Choosing AI tools for a team is harder than it looks. The category is crowded, the claims are large, and the demos tend to show the best-case scenario rather than the tenth-hour-of-use scenario that your team will actually live in. Most teams end up making the decision based on what's loudest rather than what fits. A clearer approach starts with honest questions about your team's work — and then matches tool capability to those specifics. Full article: https://askfinz.com/guides/choosing-ai-tools-for-your-team ### Turn data into a dashboard you can share — https://askfinz.com/guides/data-into-shareable-dashboards Self-serve dashboards let anyone on the team build and share charts — no BI license or SQL needed, so decisions happen faster and everyone stays in sync. Getting data into a chart that other people can see has always required more than it should. You either needed a BI tool, someone who could write SQL, or enough patience to wrangle a spreadsheet into something presentable. For most teams, that meant the people who understood the numbers weren't always the people who could share them — and decisions got made on stale exports or verbal summaries instead. Self-serve dashboards change that. When anyone on the team can turn data into a shareable visual without a specialist, the gap between a question and a clear answer collapses. Full article: https://askfinz.com/guides/data-into-shareable-dashboards ### Fine-tune and track AI models end to end — https://askfinz.com/guides/fine-tune-ai-models A fine-tuning platform that handles training runs, version tracking and evaluation, for teams who need AI built on their own data. General-purpose AI models are impressive until you need them to do something specific to your domain. A support model that doesn't understand your product. A classification model that doesn't know your categories. A summarisation model that doesn't match your house style. At that point, most teams face the same problem: fine-tuning is the right answer, but the infrastructure to do it well — track experiments, version models, evaluate outputs — is expensive and time-consuming to build yourself. Fine-tuning and model tracking are part of askFinz's [Train workspace](/apps/train), now in beta. Full article: https://askfinz.com/guides/fine-tune-ai-models ### From question to cited answer — https://askfinz.com/guides/from-question-to-cited-answer How AI with citations lets you research faster, trust the results, and share work that stands up to scrutiny — without chasing sources after the fact. Most people have had the experience of finishing a research task only to realise they can't remember where a key fact came from. The answer is there, but the trail isn't. That gap — between knowing something and being able to show where you learned it — is what makes a lot of AI-assisted research feel risky. askFinz Research is built around a different starting point: every claim stays attached to its source, from the moment you ask. Full article: https://askfinz.com/guides/from-question-to-cited-answer ### How AI model routing works (in plain English) — https://askfinz.com/guides/how-ai-model-routing-works AI model routing explained: how platforms automatically match each task to the right AI model so you get better results, without choosing one yourself. If you've used more than one AI tool, you've probably noticed that different models have different strengths. One is better at summarising documents; another is faster but handles nuance less well; a third is especially good at reasoning through complex problems. Choosing the right one for each task is possible — but it adds friction. You have to know which models exist, understand their differences, and remember to switch. Model routing removes that decision from your plate. The platform handles the match. Full article: https://askfinz.com/guides/how-ai-model-routing-works ### Keeping work private when you use AI — https://askfinz.com/guides/keeping-work-private-with-ai Private AI for business means knowing where your data goes, what controls you have, and how to use AI without exposing your team's confidential work. AI tools have become genuinely useful for professional work — but the default settings of most popular tools were designed for consumer use, not for the confidentiality expectations that come with business and client work. The gap between "useful" and "private enough for professional use" is real, and it's worth understanding before you or your team starts pasting sensitive material into a chat window. The good news is that privacy-conscious AI use isn't about choosing between capability and control. It's about understanding what the options are and picking the one that fits the work. Full article: https://askfinz.com/guides/keeping-work-private-with-ai ### A live map of aircraft, ships & satellites — https://askfinz.com/guides/live-map-aircraft-ships-satellites Track any flight, vessel, or satellite in real time from one map — without installing anything or stitching together separate live flight tracker tabs. Open a flight tracking site and you get flights. Open a vessel tracker and you get ships. Want satellites? That's a third window. If you're coordinating a shipment, watching a cargo route, or just curious where a plane overhead is headed, you already know the frustration of bouncing between three separate tools that don't share a single frame of reference. The [askFinz Map](/apps/map) puts all three layers on one canvas — live, together, now. Full article: https://askfinz.com/guides/live-map-aircraft-ships-satellites ### One sign-in for every workspace and device — https://askfinz.com/guides/one-sign-in-every-workspace Single sign-on for AI tools that actually works across every askFinz workspace and device — no per-app logins, no session drift, no access gaps. The login problem sounds trivial until you're in it. You open a new workspace, you're signed out. You switch devices, you start over. A team member needs access, you spend ten minutes figuring out which tool they need an account in. Someone leaves, and months later you discover they still had access to three systems nobody remembered they were in. Full article: https://askfinz.com/guides/one-sign-in-every-workspace ### Bug reports, feature requests, community votes — https://askfinz.com/guides/product-feedback-board How teams use a product feedback board in askFinz to collect reports, organise feature requests, and give their community a voice in what ships next. Every product team eventually faces the same problem: feedback is everywhere. Bug reports arrive by email. Feature requests come through support tickets, social posts, and direct messages. Users vote with their feet, but rarely get a channel to vote with their voice. askFinz **Feedback** is already live and built to pull that together — one place where what your community says becomes something your team can actually act on. Full article: https://askfinz.com/guides/product-feedback-board ### Talk to your spreadsheets with AI — https://askfinz.com/guides/talk-to-your-spreadsheets How AI data analysis lets you ask questions of your numbers in plain English — no formulas, no SQL, no waiting on the one person who knows the pivot table. There is always one person on the team who knows the spreadsheet. Everyone else works around them — sending requests, waiting for the column, hoping the formula is right. That bottleneck is not about the data; it is about access. AI data analysis is changing that by letting anyone on the team ask a question of their data in plain language and get a real answer back.
Full article: https://askfinz.com/guides/talk-to-your-spreadsheets ### Put your whole team's knowledge in one place — https://askfinz.com/guides/team-knowledge-in-one-place A team knowledge base powered by AI means anyone can find what your organisation already knows — without asking around or hunting through old files. Every team has a version of the same problem: the answer already exists somewhere. A colleague wrote it up six months ago, or it lives in a PDF buried in a shared drive, or the right person knows it but isn't available right now. The knowledge is there — it's just not findable. A team knowledge base changes that. When everything your team knows is in one searchable place, the question "does anyone know about X?" becomes "let me look that up." Full article: https://askfinz.com/guides/team-knowledge-in-one-place ### Use AI privately, on your own device — https://askfinz.com/guides/use-ai-privately-on-your-device Private offline AI means your sensitive work stays on your machine — no cloud upload, no third-party access, no guessing what happens to your data. Most AI tools work by sending your input to a server — a server you don't control, operated by a company whose data practices you're trusting. For personal tasks that's often fine. For work that involves confidential information, client data, or anything sensitive, the question of where your words go starts to matter. Running AI on your own device is the answer to that question. Nothing leaves the machine. Nothing is stored remotely. The capability is entirely yours. Full article: https://askfinz.com/guides/use-ai-privately-on-your-device ### What are AI tokens and context windows? — https://askfinz.com/guides/what-are-ai-tokens-and-context-windows What are tokens and context windows in AI? A plain-English guide to why they matter for how much an AI can read, remember, and cost per conversation. Two terms come up almost every time someone gets serious about using AI at work: tokens and context windows. Both sound technical, but the ideas behind them are straightforward — and understanding them changes how you use AI tools more effectively. ##### What is a token? AI language models don't read text the way you do — one word at a time. They break text into smaller pieces called tokens. Full article: https://askfinz.com/guides/what-are-ai-tokens-and-context-windows ### What is a large language model (LLM)? — https://askfinz.com/guides/what-is-a-large-language-model What is an LLM? A clear, jargon-free explanation of large language models — what they are, how they learned, and what they're actually good at. "Large language model" has become one of the most used phrases in tech, but it's often repeated without much explanation. Here's a plain-English account of what an LLM actually is, what it learned, and what that means for how you can use one. ##### What it is A large language model is a type of software trained to understand and generate text. It learned by processing enormous quantities of written language — books, articles, websites, code, and more — and finding the statistical patterns in how words and ideas relate to each other. Full article: https://askfinz.com/guides/what-is-a-large-language-model ### What is a multi-model AI platform? — https://askfinz.com/guides/what-is-a-multi-model-ai-platform What is a multi-model AI platform? A plain-English guide to why access to multiple AI models in one place produces better results and lower costs. Most people who start using AI begin with one tool: a single chatbot, a single provider, one model. That works fine for getting started. But teams that use AI seriously — across different tasks, with different priorities — tend to hit a ceiling. Not because AI isn't useful, but because no single model is best at everything. A multi-model AI platform is the answer to that ceiling. It's a product that gives you access to multiple AI models from different providers — in one place, under one interface, without needing separate subscriptions, logins, or workflows for each. Full article: https://askfinz.com/guides/what-is-a-multi-model-ai-platform ### What is an AI workspace? — https://askfinz.com/guides/what-is-an-ai-workspace What is an AI workspace? A plain-English explanation of how purpose-built AI workspaces differ from chatbots, and why teams are switching to them. "AI workspace" is a term that gets used loosely — sometimes to mean a chatbot with a nicer interface, sometimes to mean something genuinely different. It's worth being precise, because the difference matters if you're deciding whether one is worth adopting. A chatbot is a single-surface conversation. You type, it responds, you close the tab. An AI workspace is something built for sustained, varied work — multiple capabilities in one place, with memory that persists across sessions, and tools that connect to each other rather than starting from scratch each time. Full article: https://askfinz.com/guides/what-is-an-ai-workspace ### What is MCP (Model Context Protocol)? — https://askfinz.com/guides/what-is-mcp-model-context-protocol MCP (Model Context Protocol) is an open standard that lets AI assistants connect to external tools and data sources in a structured, interoperable way. AI assistants are increasingly useful on their own — but their real potential comes when they can reach outside the conversation and interact with the tools and data you already use. Model Context Protocol (MCP) is an open standard that defines how that connection works. Understanding it helps you see why AI assistants that support it are meaningfully different from ones that don't.
Full article: https://askfinz.com/guides/what-is-mcp-model-context-protocol ### What is prompt engineering? — https://askfinz.com/guides/what-is-prompt-engineering What is prompt engineering? A practical, plain-English guide to writing better AI prompts — and when it genuinely matters vs. when it doesn't. "Prompt engineering" sounds like it might require a computer science degree. It doesn't. At its core, it just means writing better instructions for an AI — being clearer, more specific, and more deliberate about what you ask and how you ask it. That said, there are real patterns and techniques that consistently produce better results, and it's worth knowing them. Full article: https://askfinz.com/guides/what-is-prompt-engineering ### What is retrieval-augmented generation (RAG)? — https://askfinz.com/guides/what-is-retrieval-augmented-generation-rag What is RAG? A plain-English explainer on retrieval-augmented generation — how it works, why it matters, and when teams use it. If you've ever asked an AI chatbot something specific — "What does our refund policy say?" or "What did the Q3 report conclude?" — and gotten a confident but wrong answer, you've encountered the core problem that retrieval-augmented generation (RAG) was designed to solve. AI language models are trained on large amounts of text up to a certain date. After that, they know nothing new. They also know nothing private — no internal documents, no company wikis, no proprietary research. RAG is the technique that bridges that gap. Full article: https://askfinz.com/guides/what-is-retrieval-augmented-generation-rag ### One AI workspace instead of ten browser tabs — https://askfinz.com/guides/one-workspace-instead-of-app-switching App-switching quietly eats your day. Here's how teams consolidate research, writing, code, and dashboards into one AI workspace — with a single login. Count the tools open in your browser right now. For most knowledge workers it's somewhere north of ten — and the cost isn't the tools themselves, it's the *gaps between them*. Every switch is a small reset: find the tab, remember where you were, copy something across, lose your train of thought. Those minutes add up. askFinz is built around a simple idea: bring the work to one place instead of carrying it between many. Full article: https://askfinz.com/guides/one-workspace-instead-of-app-switching ## Integrations (26) **Integrations** — https://askfinz.com/integrations Bring the tools your work already lives in into one searchable place. - **Airtable integration: search every base** (https://askfinz.com/integrations/airtable): Bring Airtable into askFinz Knowledge so every base, table, and record is searchable and usable in plain language. Coming to askFinz soon. - **Asana integration: search tasks and projects** (https://askfinz.com/integrations/asana): Bring Asana into askFinz Knowledge so every task, project, and goal is searchable in plain language. Coming to askFinz soon. - **BigCommerce integration: search your catalogue** (https://askfinz.com/integrations/bigcommerce): Bring BigCommerce into askFinz Knowledge so every product, order, and customer record is searchable in plain language. Coming soon. - **Box integration: search contracts and files** (https://askfinz.com/integrations/box): Bring Box into askFinz Knowledge so every folder, document, and contract is searchable in Chat and Research. Coming to askFinz soon. - **CSV upload: ask a dataset a question** (https://askfinz.com/integrations/csv): Upload any CSV into askFinz Knowledge and every row becomes searchable and usable in Chat and Research in plain language. Coming soon. - **Dropbox integration: search every file** (https://askfinz.com/integrations/dropbox): Bring Dropbox into askFinz Knowledge so every file is searchable and citable in Chat and Research. Coming to askFinz soon. - **Figma integration: search files and comments** (https://askfinz.com/integrations/figma): Bring Figma into askFinz Knowledge so every file, frame, and design decision is searchable in plain language. Coming to askFinz soon. - **GitHub integration: search repos, issues, PRs** (https://askfinz.com/integrations/github): Bring GitHub into askFinz Knowledge so repos, pull requests, issues, and docs are searchable in Chat and Research. Coming to askFinz soon. - **GitLab integration: search issues and wikis** (https://askfinz.com/integrations/gitlab): Bring GitLab into askFinz Knowledge so merge requests, issues, and wikis are searchable in Chat and Research. Coming to askFinz soon. - **Google Drive integration: search by content** (https://askfinz.com/integrations/google-drive): Bring Google Drive into askFinz Knowledge so every doc, sheet, and slide is searchable in Chat and Research. Coming to askFinz soon. - **Jira integration: search tickets and comments** (https://askfinz.com/integrations/jira): Bring Jira into askFinz Knowledge so you can search tickets, track blockers, and discuss sprint health in plain language. Coming soon. - **Linear integration: search issues and projects** (https://askfinz.com/integrations/linear): Bring Linear into askFinz Knowledge so issues, projects, and roadmap context are searchable in Chat and Research. Coming to askFinz soon. - **Microsoft Teams integration: search channels** (https://askfinz.com/integrations/microsoft-teams): Bring Microsoft Teams into askFinz Knowledge so channels, chats, and meeting notes are searchable in Research and Chat. Coming to askFinz soon. - **Notion integration: search pages and databases** (https://askfinz.com/integrations/notion): Bring Notion into askFinz Knowledge so your wikis, databases, and notes are searchable and citable in Chat and Research. Coming to askFinz soon. - **OneDrive integration: search your own files** (https://askfinz.com/integrations/onedrive): Bring OneDrive into askFinz Knowledge so every file is searchable and usable in Chat and Research. Coming to askFinz soon. - **Power BI integration: find the right report** (https://askfinz.com/integrations/power-bi): Bring Power BI into askFinz Knowledge so every dashboard, dataset, and report is searchable and citable in plain language. Coming soon. - **Proton Drive integration: search private files** (https://askfinz.com/integrations/proton-drive): Bring Proton Drive into askFinz Knowledge so your privacy-first files are searchable, without compromising control. Coming to askFinz soon. - **Salesforce integration: search your CRM** (https://askfinz.com/integrations/salesforce): Bring Salesforce into askFinz Knowledge so every account, opportunity, and contact is searchable in plain language. Coming soon. - **SAP integration: search records in plain words** (https://askfinz.com/integrations/sap): Bring SAP into askFinz Knowledge so every record, report, and process is searchable in plain language across your organisation. Coming soon. - **SharePoint integration: search the intranet** (https://askfinz.com/integrations/sharepoint): Bring SharePoint into askFinz Knowledge so your intranet, wikis, and shared libraries are searchable in Chat and Research. Coming to askFinz soon. - **Shopify integration: search orders and products** (https://askfinz.com/integrations/shopify): Bring Shopify into askFinz Knowledge so every order, product, and customer record is searchable in plain language. Coming to askFinz soon. - **Slack integration: find decisions in threads** (https://askfinz.com/integrations/slack): Bring Slack into askFinz Knowledge so decisions buried in threads are searchable and citable in Research and Chat. Coming to askFinz soon. - **SQL database search without writing queries** (https://askfinz.com/integrations/sql-database): Bring any SQL database into askFinz Knowledge so every table and record is searchable without writing queries. Coming to askFinz soon. - **Trello integration: search every board** (https://askfinz.com/integrations/trello): Bring Trello into askFinz Knowledge so every board, card, and checklist is searchable with AI. Coming to askFinz soon. - **Zendesk integration: search every ticket** (https://askfinz.com/integrations/zendesk): Bring Zendesk into askFinz Knowledge so every ticket, macro, and resolution is searchable in plain language. Coming to askFinz soon. - **Zoom integration: search meeting transcripts** (https://askfinz.com/integrations/zoom): Bring Zoom into askFinz Knowledge so meeting transcripts and recordings are searchable in askFinz. Coming to askFinz soon. ## Comparisons (26) **Comparisons** — https://askfinz.com/compare Honest comparisons of askFinz and the tools you already know. ### askFinz vs Amazon Bedrock Web Search — https://askfinz.com/compare/askfinz-vs-amazon-bedrock-web-search A fair askFinz vs Amazon Bedrock Web Search comparison — Amazon's own new web index against a standalone workspace on an index askFinz reads and holds. **Quick answer.** Both sides here own their index, which makes this the least one-sided page on the site. Amazon launched its own web search inside Bedrock in August 2026 and has not published a per-query rate. askFinz publishes three flat rates — $0.75 top-up, $1.00 with the extension, $3.50 standalone — as a standalone workspace rather than a platform feature. Full article: https://askfinz.com/compare/askfinz-vs-amazon-bedrock-web-search ### askFinz vs Apify — https://askfinz.com/compare/askfinz-vs-apify A fair askFinz vs Apify comparison — a marketplace of scrapers you configure and run per job against a single standing index you can just search. **Quick answer.** Apify is a marketplace of task-specific scrapers you pick, configure and run per job — someone has often already built the one you need. askFinz maintains a single index read continuously, so a question is answered against what is already there. Apify answers the question you configured; askFinz answers ones you did not plan for. Full article: https://askfinz.com/compare/askfinz-vs-apify ### askFinz vs Brave Search API — https://askfinz.com/compare/askfinz-vs-brave-search-api A fair askFinz vs Brave Search API comparison — an independent index sold as an API against a workspace built on an index askFinz reads and holds itself. **Quick answer.** Brave is one of the few names here that genuinely owns what it sells — an independent index built without Google or Bing underneath it. So the fight is not about ownership. It is price and shape: Brave publishes $5.00 per 1,000 searches ($4.00 on its answers tier) and returns results; askFinz returns the matched passage and the answer from $0.75. Full article: https://askfinz.com/compare/askfinz-vs-brave-search-api ### askFinz vs Bright Data — https://askfinz.com/compare/askfinz-vs-bright-data A fair askFinz vs Bright Data comparison — a proxy network for reaching the web yourself against an index that has already read it and holds the result. **Quick answer.** Bright Data gets your traffic to the page. askFinz has already read the page and holds the result. One sells access; the other sells an answer. If your job is reaching a specific defensive site yourself and controlling exactly what you extract, Bright Data is built for that and askFinz cannot do it. Full article: https://askfinz.com/compare/askfinz-vs-bright-data ### askFinz vs ChatGPT — https://askfinz.com/compare/askfinz-vs-chatgpt A fair askFinz vs ChatGPT comparison — a mature conversational assistant against a multi-model workspace where research, code and filing share one login. **Quick answer.** ChatGPT is an exceptional conversational assistant with a large ecosystem behind it. askFinz is a multi-model workspace for work that does not stay in a chat window — research with sources attached, code, and a filed record, in one login. If chat is the right shape for your work, ChatGPT is the more mature product. Full article: https://askfinz.com/compare/askfinz-vs-chatgpt ### askFinz vs Claude — https://askfinz.com/compare/askfinz-vs-claude A fair askFinz vs Claude comparison — a focused single-family assistant against a multi-model workspace that includes Claude and adds workspaces beyond chat. **Quick answer.** Claude is one of the most capable assistants available, and claude.ai is a deliberately focused chat product. askFinz is a multi-model workspace that includes Claude alongside other leading models and adds Research, Code, Search and Storage. If chat is the right shape for your work, claude.ai is the cleaner tool. Full article: https://askfinz.com/compare/askfinz-vs-claude ### askFinz vs Common Crawl — https://askfinz.com/compare/askfinz-vs-common-crawl A fair askFinz vs Common Crawl comparison — a free, periodically-published public web archive against an index askFinz reads continuously and files by type. **Quick answer.** Common Crawl is free and enormous — a periodic public archive of the web as raw WARC files, and the backbone of a great deal of open research. It is a snapshot from whenever that crawl ran, and it arrives unstructured. askFinz reads continuously and files what it reads by document type, as a product rather than an archive. Full article: https://askfinz.com/compare/askfinz-vs-common-crawl ### askFinz vs DataForSEO — https://askfinz.com/compare/askfinz-vs-dataforseo A fair look at DataForSEO vs askFinz — why $0.60 per 1,000 search-engine results is a real number, what it buys, and what it cannot reach. **Quick answer.** DataForSEO sells search-engine results at $0.60 per 1,000 — the cheapest rate anywhere in this comparison, and a genuine one. It is that cheap because it holds no index: it relays what the engines show. askFinz answers from an index it reads and holds itself, returning the matched passage with the answer, from $0.75 per 1,000. Different products, honestly priced. Full article: https://askfinz.com/compare/askfinz-vs-dataforseo ### askFinz vs Exa — https://askfinz.com/compare/askfinz-vs-exa A fair askFinz vs Exa comparison — a semantic search API priced per call, with page text billed separately, against a workspace on an index askFinz holds. **Quick answer.** Both run their own index; the difference is what a call ends at. Exa is a semantic search API — $5.00–$7.00 per 1,000 searches, with the page text behind a result billed separately at $1.00 per 1,000 pages. askFinz returns the matched passage with the answer in one step, from $0.75 per 1,000, as a workspace rather than an API. Full article: https://askfinz.com/compare/askfinz-vs-exa ### askFinz vs Firecrawl — https://askfinz.com/compare/askfinz-vs-firecrawl A fair askFinz vs Firecrawl comparison — an open-source scraping API for building your own pipeline against a maintained index you can search directly. **Quick answer.** Firecrawl turns a URL into clean, LLM-ready markdown. askFinz answers a question from an index it already read. They sit at different layers: Firecrawl is infrastructure you build a retrieval system on top of, and askFinz is a retrieval system. If you need clean content for your own pipeline, Firecrawl is the right tool and askFinz is not. Full article: https://askfinz.com/compare/askfinz-vs-firecrawl ### askFinz vs Google Gemini — https://askfinz.com/compare/askfinz-vs-google-gemini A fair askFinz vs Google Gemini comparison — AI inside Google Workspace against a platform-agnostic workspace for research, code and automation. **Quick answer.** Gemini is strongest inside Google Workspace — Docs, Sheets, Gmail, Meet, Drive — and is genuinely ahead on multimodal work across text, image, audio and video. askFinz is platform-agnostic, brings several model families together, and adds Research, Code and Workflow. If your work lives in Drive, Gemini is the better fit. Full article: https://askfinz.com/compare/askfinz-vs-google-gemini ### askFinz vs Google Vertex AI Search — https://askfinz.com/compare/askfinz-vs-google-vertex-ai-search A fair askFinz vs Google Vertex AI Search comparison — enterprise search priced across three dimensions against a flat rate on an index askFinz holds. **Quick answer.** Vertex AI Search is an enterprise product priced across three dimensions at once — per query, per volume of data indexed, and per grounding call — so no single per-1,000 figure describes it. askFinz publishes one flat rate per search against an index it already holds: $0.75 as a top-up, $1.00 with the extension, $3.50 standalone. Full article: https://askfinz.com/compare/askfinz-vs-google-vertex-ai-search ### askFinz vs Grok — https://askfinz.com/compare/askfinz-vs-grok A fair askFinz vs Grok comparison — a fast conversational assistant close to X against a multi-model workspace with research, code and a filed record. **Quick answer.** Grok is xAI's assistant, with a distinct conversational style, tight integration with X, a DeepSearch mode and code execution in chat. askFinz is a multi-model workspace that adds Research, Code, Storage and Projects around the answer. If you live on X and want a fast assistant close to that feed, Grok is the easier fit. Full article: https://askfinz.com/compare/askfinz-vs-grok ### askFinz vs Keiro — https://askfinz.com/compare/askfinz-vs-keiro A fair askFinz vs Keiro comparison — the closest competitor on price, matched call-for-call on what page text actually costs at each tier. **Quick answer.** Keiro is the closest competitor askFinz has on price. Compared fairly — search that returns page text against search that returns page text — Keiro is $3.00–$9.00 per 1,000 depending on plan, askFinz $0.75–$3.50. Keiro's links-only tier at $1.00 per 1,000 is genuinely cheaper, and it is a thinner product. Full article: https://askfinz.com/compare/askfinz-vs-keiro ### askFinz vs Linkup — https://askfinz.com/compare/askfinz-vs-linkup A fair askFinz vs Linkup comparison — a flat-rate search API for agents against a workspace built on an index askFinz reads and holds itself. **Quick answer.** Linkup is a search API with a deliberately flat rate — about $5.00 per 1,000 requests whether you make ten or ten thousand, so next month's bill is knowable today. askFinz is a search workspace on an index it reads and holds, returning the matched passage with the answer from $0.75 per 1,000. One is predictability; the other is a shorter chain. Full article: https://askfinz.com/compare/askfinz-vs-linkup ### askFinz vs Microsoft Copilot — https://askfinz.com/compare/askfinz-vs-microsoft-copilot A fair askFinz vs Microsoft Copilot comparison — AI inside Microsoft 365 and the Graph against a platform-agnostic multi-model workspace. **Quick answer.** Copilot's advantage is depth inside Microsoft 365: it can answer from your own emails, meetings and documents through the Microsoft Graph, which no platform-agnostic tool can replicate. askFinz is a multi-model workspace for work that starts with a question rather than a file, outside any one suite. Full article: https://askfinz.com/compare/askfinz-vs-microsoft-copilot ### askFinz vs Notion AI — https://askfinz.com/compare/askfinz-vs-notion-ai A fair askFinz vs Notion AI comparison — AI over the docs you have already written against a workspace for the research that happens before they exist. **Quick answer.** Notion AI works with what you have already written — your pages, databases and wikis. askFinz works on the stage before that, where the material does not exist yet and has to be gathered, sourced and shaped. Many teams use both: askFinz to gather, Notion to store and share. Full article: https://askfinz.com/compare/askfinz-vs-notion-ai ### askFinz vs Perplexity — https://askfinz.com/compare/askfinz-vs-perplexity A fair askFinz vs Perplexity comparison — a fast cited answer engine against a workspace where the answer becomes work, on an index askFinz holds itself. **Quick answer.** Perplexity gives you a fast, cited answer from live web search and is very good at it. askFinz answers from an index it reads and holds itself, and keeps going: the answer becomes a cited brief, a project or a filed reference in the same login. If a quick sourced summary is what you need, Perplexity is the more focused tool. Full article: https://askfinz.com/compare/askfinz-vs-perplexity ### askFinz vs SearchAPI — https://askfinz.com/compare/askfinz-vs-searchapi A fair look at SearchAPI vs askFinz — a low-cost multi-engine relay at $1.00–$4.00 per 1,000 against querying an index askFinz reads and holds itself. **Quick answer.** SearchAPI relays Google, Bing, YouTube and other engines as structured JSON at $1.00–$4.00 per 1,000 calls, depending on engine and endpoint. askFinz answers from an index it reads and holds itself, returning the matched passage with the answer from $0.75 per 1,000. The cheap rate is real, and it is cheap because there is no index behind it. Full article: https://askfinz.com/compare/askfinz-vs-searchapi ### askFinz vs SERP APIs — https://askfinz.com/compare/askfinz-vs-serp-apis A fair look at SERP APIs vs askFinz — renting a search engine's results page against querying an index askFinz reads and holds itself. **Quick answer.** A SERP API sends your query to Google or Bing, scrapes the results page and returns it as JSON — you are renting someone else's ranking. askFinz answers from an index it reads and holds itself, returning the matched passage with the answer. If you need to know what Google ranks today, a SERP API is the right tool and askFinz is not. Full article: https://askfinz.com/compare/askfinz-vs-serp-apis ### askFinz vs SerpApi — https://askfinz.com/compare/askfinz-vs-serpapi A fair askFinz vs SerpApi comparison — structured search-engine results at $25.00, or $9.17 at volume, per 1,000 against a workspace on an index askFinz holds. **Quick answer.** SerpApi reproduces what Google or Bing is showing right now, as clean JSON, for $25.00 per 1,000 on its entry plan and $9.17 at 30,000 a month. askFinz does not relay anyone's results page — it answers from an index it reads and holds itself, returning the matched passage with the answer from $0.75 per 1,000. Different jobs at very different prices. Full article: https://askfinz.com/compare/askfinz-vs-serpapi ### askFinz vs Serper — https://askfinz.com/compare/askfinz-vs-serper A fair look at Serper vs askFinz — a fast Google-results relay for developers against querying an index askFinz reads and holds itself. **Quick answer.** Serper is a fast way to get Google's results page as clean JSON — popular in RAG and agent pipelines that just need "what does Google say". askFinz holds its own index and returns the matched passage with the answer. There is no price column on this page: Serper does not publish rates in a form that compares honestly, and a number from anywhere but its own page is not worth repeating. Full article: https://askfinz.com/compare/askfinz-vs-serper ### askFinz vs Tavily — https://askfinz.com/compare/askfinz-vs-tavily A fair askFinz vs Tavily comparison — the default search API for LLM agents against a workspace built on an index askFinz reads and holds itself. **Quick answer.** Tavily is a search API you call from inside an agent you are building. askFinz is a finished search workspace on an index it reads and holds itself. Tavily publishes $8.00 per 1,000 searches and hands your code results to reason over; askFinz returns the matched passage with the answer, from $0.75 per 1,000. Full article: https://askfinz.com/compare/askfinz-vs-tavily ### askFinz vs Web Scraping APIs — https://askfinz.com/compare/askfinz-vs-web-scraping-apis A fair look at web scraping APIs vs askFinz — building your own retrieval pipeline against drawing on an index askFinz already reads and maintains. **Quick answer.** A web scraping API is URL in, clean content out — the raw material for a retrieval system you then build. askFinz is that system, already built and already reading. If you are building your own index on purpose, a scraping API is the right layer and askFinz is not a substitute at any price. Full article: https://askfinz.com/compare/askfinz-vs-web-scraping-apis ### askFinz vs You.com Search API — https://askfinz.com/compare/askfinz-vs-you-com A fair askFinz vs You.com Search API comparison — a configurable results API at $5.00 per 1,000 against a workspace on an index askFinz reads and holds. **Quick answer.** You.com's Search API lets a caller dial the result count from 1 to 100 in a single request, at $5.00 per 1,000 searches. askFinz is not tunable that way: it returns the matched passage and the answer, already assembled, from $0.75 per 1,000. One gives you control over the raw material; the other gives you the finished thing. Full article: https://askfinz.com/compare/askfinz-vs-you-com ### Bing Search API Alternative — https://askfinz.com/compare/bing-search-api-alternative Bing's Search API was retired on 11 August 2025. If you built on it, here is a fair look at askFinz as an alternative — a workspace on an index it holds itself. **Quick answer.** Microsoft retired the Bing Search API on 11 August 2025, and much of the search-API market was quietly built on top of it. askFinz is not a drop-in swap for an endpoint — it is a product on an index it reads and holds, returning the matched passage with the answer from $0.75 per 1,000. If you need a literal replacement call, evaluate the direct successors instead. Full article: https://askfinz.com/compare/bing-search-api-alternative ## Research notes (8) **Research notes** — https://askfinz.com/research Short writing on what we believe, what we change our minds about, and how we read the work. ### A workshop, not a chatbot — https://askfinz.com/research/a-workshop-not-a-chatbot We argued for a single blank box, and rejected it. Here is the argument that lost, why it lost, and what the decision costs us. The design that nearly became askFinz was one blank box. One input, one thread, everything behind it. It was the cleanest thing on the table and we did not build it. This note is about why, and about what we gave up to avoid it — because the argument for the blank box is genuinely strong and we lost sleep over it. ##### The case for the box, made properly Start with the version that nearly won, because a rejected approach argued weakly is not a rejected approach at all. Full article: https://askfinz.com/research/a-workshop-not-a-chatbot ### Owning your tools again — https://askfinz.com/research/owning-your-tools-again Count the layers of your working day that someone else can change without asking. For most professionals it is five out of six — and the honest fix is not "own everything", which nobody can. Count the layers your working day runs on. Your judgement, your files, your history and context, the interface, the capability, the price. For most professionals, five of those six can change next Tuesday without anyone asking. That is the whole argument. The rest of this note is about why "own everything" is not the answer, and what the achievable answer actually looks like. Full article: https://askfinz.com/research/owning-your-tools-again ### Software should earn its keep — https://askfinz.com/research/software-should-earn-its-keep A demo shows you the first time. Real work is the hundredth. Almost every design decision that matters is invisible in the first and decisive in the hundredth. A demo shows you the first time you use something. Real work is the hundredth. Almost every decision that determines whether a tool is worth keeping is invisible in the first and decisive in the hundredth. That gap has a name in our heads: demo-ware. Software that earns attention without earning its keep. ##### What the demo structurally cannot show The problem with optimising for demonstrations is not that demos are dishonest. Most are not. It is that the format selects, and it selects against exactly the properties that make a tool survivable. Full article: https://askfinz.com/research/software-should-earn-its-keep ### Speed is a feature, trust is the product — https://askfinz.com/research/speed-is-a-feature-trust-is-the-product Every latency benchmark measures the wrong half of the clock. The wait is visible and the checking is not — which is why the faster answer is routinely the slower one to use. Every latency benchmark in this industry measures the same half of the clock: the part between your question and the first word of the answer. It is the half you can see, and it is not the half that decides anything. The other half is the checking. It happens after the benchmark has stopped, inside the reader, and it is frequently longer than the wait it followed. Full article: https://askfinz.com/research/speed-is-a-feature-trust-is-the-product ### We tell you which model wrote your answer — https://askfinz.com/research/tell-you-who-wrote-the-answer Hiding the model is the industry default and it is a design choice, not a neutral one. It asks you to extend more trust than the situation earns. The industry default is to hide the model. The answer arrives from nowhere in particular — no name on the door, no indication of what produced it or what that thing is bad at. The interface is polished specifically so you stop asking. That is a design choice, not a neutral state, and it has a cost the person paying it cannot see. Full article: https://askfinz.com/research/tell-you-who-wrote-the-answer ### The case against one big model — https://askfinz.com/research/the-case-against-one-big-model The argument is not that more models are better. It is that being structurally unable to use anything else is a liability disguised as simplicity. The argument here is narrower than the title. It is not that more models are better, or that every question needs a committee. Most of the time one well-chosen approach is exactly right. It is that choosing to be structurally *unable* to use anything else is a liability, and it is a liability that reads as simplicity right up until the day it does not. Full article: https://askfinz.com/research/the-case-against-one-big-model ### The hidden cost of switching tabs — https://askfinz.com/research/the-cost-of-switching-tabs The expensive part of a context switch is not the switch. It is the climb back — and the climb never returns you to where you stopped. The expensive part of a context switch is not the switch. The switch takes a second. The expensive part is the climb back — and the climb never returns you to the height you left from. That is the whole shape of the problem, and it is why the obvious fixes do not work. ##### Nobody thinks of themselves as a tab-switcher They think of themselves as someone getting work done. The tabs are infrastructure: the route between having a question and finding an answer, between noticing something and doing something about it. Full article: https://askfinz.com/research/the-cost-of-switching-tabs ### The web became the operating system — https://askfinz.com/research/the-web-became-the-operating-system You noticed it when a new laptop took twenty minutes to become useful. The browser stopped being where you look things up and became where the work is — and the counter-argument is stronger than most people admit. You noticed when you got a new laptop and were fully operational in twenty minutes, because almost nothing needed installing. That is the moment the shift was already finished — not announced, just complete. The browser stopped being the place you look things up and became the place the work is. What follows is what that implies for anything built now, and where the counter-argument is stronger than people building for the web usually admit. Full article: https://askfinz.com/research/the-web-became-the-operating-system ## Infrastructure Full details: https://askfinz.com/infrastructure askFinz doesn't run its own data centers — it builds on best-in-class providers, described here by function and city. **Live stream ingest** (European Union (Finland)) Receives and packages live video before it reaches viewers. Certifications: ISO/IEC 27001:2022, BSI C5 Type 2, KRITIS / NIS-2, PCI DSS 4.0, Audited TOMs **Source code & version control** (European Union (Netherlands)) Stores and versions the platform's source code and build history. Certifications: ISO/IEC 27001, ISO/IEC 27017, ISO/IEC 27018, ISO/IEC 27701, ISO 22301, ISO 9001, SOC 1 / 2 / 3, CSA STAR, PCI DSS, GDPR **Primary object storage** (European Union (Netherlands)) Holds your files, media and encrypted data at rest. First-line storage for every upload and workspace asset. Certifications: SOC 2 Type 2, ISO 27001, HIPAA, GDPR & UK GDPR, CCPA / CPRA, PCI-DSS, GovRAMP, TX-RAMP, TPN Blue Shield, HECVAT, VPAT / Section 508 **Object storage backup (live mirror)** (European Union (Germany)) Live mirror of all primary object storage — syncs every 60 seconds. Activates automatically if primary storage is unavailable, with instant failover and no data loss beyond the last 60-second window. Certifications: SOC 2 Type 2, ISO/IEC 27001:2022, HIPAA, PCI, GDPR, SEC / FINRA, Data Center Security **Media & file storage** (European Union (Netherlands)) Serves uploaded media and documents from close to you. Certifications: ISO 27001:2022, ISO 27701:2019, ISO 27018:2019, ISO 27017:2015, SOC 2 Type II, PCI DSS 4.0, FedRAMP Moderate, GovRAMP, C5:2020, EU Cloud CoC, Global CBPR / PRP **Content delivery & DNS** (Global edge — 300+ cities) Routes every request to the nearest edge and resolves our domains — the reason pages load fast wherever you are. Certifications: ISO 27001 / 27701, SOC 2 Type II, C5 Type 2, HIPAA, PCI DSS 4.0.1, CSA STAR, ENS, IRAP, ISMAP, Cyber Essentials, EU Cloud CoC **SMS & voice communications** (Global carrier-grade data centers) Delivers verification codes, alerts and voice calls. Certifications: ISO 27001, SOC 1 / 2 Type II, PCI DSS, HIPAA, HDS, NIST 800-53 / FISMA High, ITAR, TISAX, Uptime Tier, ISO 22301 / 20000 / 9001, Climate Neutral DC Pact **Transactional email** (European Union (Ireland)) Sends account, security and notification emails. Certifications: SOC 2 Type II, GDPR, TLS 1.3, Encryption at rest, Point-in-time backups, Annual pen-testing **Payments & billing** (European Union (Ireland)) Processes subscriptions and payments — card details go straight to a certified processor, never to askFinz. Certifications: PCI DSS Level 1, SOC 1 / 2 Type II, SOC 3, ISO/IEC 27001, PSD2 / SCA, 3-D Secure, GDPR, Global CBPR / PRP, Encryption at rest ### Compliance glossary #### Information security management - **ISO/IEC 27001**: The international standard for an Information Security Management System (ISMS).. Our providers run a systematic, independently audited security program, so your data sits on rigorously managed foundations. - **ISO/IEC 27017**: Cloud-specific security controls that extend ISO 27001.. Cloud services we build on follow controls designed for cloud risks like tenant isolation and admin operations. - **SOC 2 Type II**: An AICPA audit of security, availability and confidentiality controls measured over a period of time.. Independent proof the providers' controls actually operate day-to-day — not just on paper. - **SOC 1**: An AICPA report on controls relevant to financial reporting.. Assurance around billing- and finance-related processing. - **SOC 3**: A plain, publicly shareable version of the confidential SOC 2 audit.. Lets a provider share independent proof of its security controls openly — no confidentiality agreement required. - **CSA STAR**: The Cloud Security Alliance's Security, Trust, Assurance & Risk program.. Cloud-specific, registry-published transparency on a provider's security posture. - **BSI C5**: Germany's Federal Office for Information Security (BSI) cloud criteria catalogue; Type 2 tests operating effectiveness.. A rigorous EU cloud-security benchmark that incorporates ISO 27001. - **Audited TOMs**: Technical & Organizational Measures under GDPR Art. 32, externally audited.. Documented, verified safeguards specifically around personal-data processing. - **Cyber Essentials**: A UK NCSC-backed baseline cyber-security certification.. Independently verified baseline cyber hygiene. - **TISAX**: The Trusted Information Security Assessment Exchange.. Shared, audited information-security assurance across vendors. #### Privacy & data protection - **GDPR / UK GDPR**: The EU and UK General Data Protection Regulation.. Lawful processing and your data-subject rights are honored across the EU and UK. - **EU Model Clauses**: Standard Contractual Clauses for lawful international data transfers.. A lawful basis for any cross-border data flow. - **ISO/IEC 27701**: An international privacy-management standard that extends ISO 27001 from security into how personal data is handled.. Shows a provider runs privacy as a formal, audited program — and their evidence directly supports our own GDPR compliance. - **ISO/IEC 27018**: A code of practice for protecting personal data (PII) in public clouds.. Constrains how providers handle personal data — e.g. it isn't used for advertising. - **EU Cloud CoC**: A GDPR Article 40 approved code of conduct for cloud providers.. The provider's GDPR compliance is independently verified for its cloud services. - **CCPA / CPRA**: California's consumer privacy laws.. Privacy rights — access, deletion and opt-out — for California users. - **Global CBPR / PRP**: International Cross-Border Privacy Rules & Privacy Recognition for Processors certifications.. A recognized framework for moving data across borders responsibly. #### Payments & regulated data - **PCI DSS**: The Payment Card Industry Data Security Standard (v4.0).. Card data is handled only in a PCI-compliant environment — safe billing and payments. - **PCI DSS Level 1**: The highest PCI DSS tier, for processors handling the largest card volumes, audited annually by a Qualified Security Assessor.. Card payments run through a top-tier-certified processor — your card details never touch askFinz. - **PSD2 / SCA**: The EU Payment Services Directive 2 and its Strong Customer Authentication requirement.. European card payments are authenticated to EU regulatory standards, such as a second factor at checkout. - **3-D Secure**: An EMV authentication protocol (3DS2) that verifies the cardholder during online payments.. Adds a fraud check and shifts liability, protecting you and us on card payments. - **HIPAA**: The US health-data protection law (Health Insurance Portability and Accountability Act); a Business Associate Agreement is available. Covers protected health information (PHI) and ePHI in compliance with HIPAA and HITECH, as administered by HHS.. Lets us and healthcare customers handle protected health information where needed, such as the med workspace. - **CJIS**: Criminal Justice Information Services — standards set by a division of the US FBI for the privacy, security, durability and protection of Criminal Justice Information (CJI) and other critical data.. Storage infrastructure supports law-enforcement and justice-sector customers who must maintain CJIS compliance. - **FERPA**: The Family Educational Rights and Privacy Act — imposes specific technical and administrative requirements for education IT planners, InfoSec organizations and compliance officers receiving U.S. Department of Education aid.. Educational institutions and EdTech customers can store and process student data in compliance with FERPA. - **SEC / SEA**: U.S. Securities and Exchange Commission and Securities Exchange Act rules (17 CFR 240.17a-4) — third-party record-keeping services must provide an undertaking letter to customer organizations. Effective May 2023.. Financial-services customers who are SEC-regulated can obtain an alternate undertaking letter for compliant record retention. - **HDS**: The EU 'Health Data Hosting' (Hébergeur de Données de Santé) certification.. Health data can be hosted within the EEA to a regulated standard. - **ITAR**: US International Traffic in Arms Regulations data-handling controls.. Providers support controlled-data handling, e.g. US-person access restrictions. #### Government & national security programs - **FedRAMP**: US federal cloud security authorization (Moderate).. A government-grade security baseline underpins our edge and storage. - **NIST 800-53 / FISMA**: The US federal security control catalogue and risk baseline (High).. A stringent, well-known control baseline underpins the infrastructure. - **GovRAMP**: US state & local government cloud authorization (formerly StateRAMP).. Public-sector-grade assurance. - **TX-RAMP**: The Texas Risk & Authorization Management Program.. Meets Texas public-sector security requirements. - **KRITIS / NIS-2**: German & EU critical-infrastructure operator obligations, certified per §8a BSIG.. Infrastructure held to critical-service resilience and security duties. - **ENS**: Spain's Esquema Nacional de Seguridad (National Security Framework).. Meets the Spanish national security framework. - **IRAP**: Australia's Information Security Registered Assessors Program.. Australian government-grade security assessment. - **ISMAP**: Japan's government cloud security assessment program.. Japanese public-sector-grade assurance. #### Reliability, quality & sustainability - **ISO 22301**: The standard for business continuity management.. Providers plan for disruptions, so the platform stays available through incidents. - **ISO/IEC 20000-1**: The IT service management standard.. Mature, repeatable operations behind the services we depend on. - **ISO 9001**: The quality management system standard.. Consistent, documented service quality. - **Uptime Tier**: Uptime Institute Tier certification for data-center design, facility and operations.. Physical infrastructure engineered for high availability. - **Climate Neutral DC Pact**: A European pledge for carbon-neutral data centers by 2030.. Greener hosting for your workloads. - **TPN**: Trusted Partner Network (Blue Shield), aligned to MPA content-security best practices.. Media and content stored to film-industry security standards. - **HECVAT**: The Higher-Education Community Vendor Assessment Tool.. Vetted for use by universities and research institutions. - **VPAT / Section 508**: A Voluntary Product Accessibility Template against Section 508 guidelines.. Services remain accessible to users with disabilities. #### Provider data-protection practices - **TLS 1.3**: The latest transport-layer encryption protocol.. Data in transit is strongly encrypted everywhere it crosses a network. - **Encryption at rest**: Stored data is encrypted, with row-level encryption for sensitive tables.. Stored data is unreadable if storage media are ever compromised. - **Point-in-time backups**: 30-day retention, globally replicated backups.. Recoverability against data loss or a regional outage. - **Annual pen-testing**: Third-party offensive security testing at least annually.. Vulnerabilities are found and fixed proactively. ## Company & trust - About (https://askfinz.com/about): The company, its structure, and the principles behind it. A subsidiary of PAUL V | Holdings. - Trust centre (https://askfinz.com/trust): Routing transparency — which model ran, which provider, why. - Security (https://askfinz.com/security): Security practices, controls, and the ongoing audit programme. - Live status (https://askfinz.com/status): Real-time platform health per service. - Brand (https://askfinz.com/brand): Logo files, brand guidelines, and visual identity. - Press (https://askfinz.com/press): News, coverage and partnerships — media kit and press contact. - Access (https://askfinz.com/access): The identity layer — single sign-on, sessions, billing, devices and recovery across every workspace and device. - Careers (https://askfinz.com/careers): Open roles at askFinz. - Changelog (https://askfinz.com/changelog): Recent platform updates, new workspaces, and shipped features. - Contact (https://askfinz.com/contact): Get in touch with the team. - Beta launch raffle terms (https://askfinz.com/raffle): Terms and conditions for the askFinz beta launch raffle. One verified signup = one entry. ## Legal (13 documents) Index: https://askfinz.com/legal - Consumer Terms of Service: https://askfinz.com/legal/terms - Commercial Terms of Service: https://askfinz.com/legal/terms/commercial - Privacy Policy: https://askfinz.com/legal/privacy - Cookie Policy: https://askfinz.com/legal/cookie-policy - Health Data Privacy Policy: https://askfinz.com/legal/health-data-privacy - Data Processing Addendum: https://askfinz.com/legal/data-processing - Applicant Privacy Policy: https://askfinz.com/legal/applicant-privacy - Acceptable Use Policy: https://askfinz.com/legal/aup - Refund Policy: https://askfinz.com/legal/refund-policy - Security Policy: https://askfinz.com/legal/security - Responsible Disclosure Policy: https://askfinz.com/legal/responsible-disclosure - Service Level Agreement: https://askfinz.com/legal/sla - Disclaimer: https://askfinz.com/legal/disclaimer ## Get started - Request access: https://askfinz.com/beta — join the private-access waitlist. - Pricing: https://askfinz.com/pricing — choose a plan. - API access: https://askfinz.com/api — programmatic access to the router, agents, and citation layer. ## Alternate brand names askFinz, askfinz, AskFinz, Askfinz, ask finz, ask finn, askfinn, askfin, finz, finz AI, finz LLM.