At a glance
Web scraping APIs vs askFinz
Row by row — reach, freshness and what you get back.
| Compared on | Web scraping APIs | askFinz |
|---|---|---|
| What you get | Raw page content, as markdown or JSON, per request | An answer grounded in an index askFinz already holds |
| Who builds the retrieval pipeline | You — chunking, embedding, ranking, refresh | Already built and running |
| Freshness | As often as you choose to re-crawl | Continuous reading, not a scheduled rebuild |
| Reaching sites that fight automation | Your responsibility, often via a proxy layer | Real browser sessions rather than a rented proxy pool |
| Structure | Pages come back largely undifferentiated | Filed as what it is — a filing, a standard, a listing |
| Best at | Teams building a custom pipeline | Teams who want the answer, not the pipeline |
Swipe the table sideways to see both columns.
What web scraping APIs are
Firecrawl, Apify, Bright Data and others each take their own approach, but the shape is similar: you send a URL or a crawl instruction, they handle rendering and anti-bot defences, and you get content back to store, chunk, embed and search yourself. Some are open source and self-hostable. All of them solve the fetch, and all of them leave retrieval — freshness, deduplication, ranking, keeping an index current — to you.
What askFinz is
askFinz does not hand you raw pages to build with. It runs its own web index, read continuously and kept current, with a Search workspace, a browser extension and research agents on top. A question returns the matched passage together with the answer. askFinz does not sell index access as a raw feed or a general-purpose scraping API.
The part after the fetch
The work most people actually want is not "get me clean HTML" — it is "answer this using what is out there, and show me where it came from". Between those two sentences sits a set of decisions somebody has to keep making: how often to re-read a page, how to stop a headless fetch being fingerprinted and refused before the page loads, and how to turn a pile of scraped documents into something that ranks well and stays current.
Where a scraping API is simply correct
If your job is genuinely "fetch this URL and give me clean text for my own system", a dedicated scraping API is the right tool and a good one will save real engineering time. Building a search or retrieval product from scratch is a legitimate reason to reach for one, and askFinz will not do that job — it cannot take a URL and hand back its content.
Two different jobs
These are not substitutes. Here is which job each one is for.
Choose a web scraping API if
- Your product reads pages that users or agents choose at runtime, so the URL is not knowable in advance.
- You are building your own index deliberately and want the fetch layer solved without owning it.
- You need the full page, not a passage — full text, structure, links, everything.
- Self-hosting matters, and you want an option with no vendor in the request path.
- Your product's value is in how you chunk, embed and rank, so raw content is exactly what you want to buy.
Choose askFinz if
- You want the answer, not the raw material to build one from.
- You do not want crawling, refresh cadence and anti-bot handling as a permanent engineering commitment.
- You want the passage the answer came from, checkable, alongside the answer.
- You want content filed by what it is — a filing, a standard, a listing — rather than as undifferentiated pages.
- The answer needs somewhere to go afterwards — Research, Storage, a project.
FAQ
Questions people ask
The things people actually ask before choosing between Web Scraping APIs and askFinz.
5 questions · open one to read the answer
No. It answers from the index it maintains; it does not fetch arbitrary URLs on request.
No. There is no raw feed and no general-purpose scraping API.
It reads through real browser sessions rather than a rented proxy pool.
Sometimes, and honestly so — if you already have the retrieval expertise and the corpus you need is narrow, a scraping API plus your own index can be cheaper and more controllable than any product.
Chunking, embedding, ranking, deduplication, refresh scheduling and evaluation. That is the retrieval system, and it is the part that does not stop needing attention.
See how the index works, browse what is in it, or read the fuller comparison against traditional search and RAG infrastructure. Join the beta and try Search against a real question.