At a glance
Google Vertex AI Search vs askFinz
Row by row — what a call buys on each side.
| Compared on | Google Vertex AI Search | askFinz |
|---|---|---|
| What you buy | An enterprise search platform inside Google Cloud | A Search workspace, browser extension and research agents |
| Rate per 1,000 queries | $1.50 Search Standard · $4.00 Search Enterprise — before storage and grounding | $0.75 top-up · $1.00 with the extension or a paid plan · $3.50 standalone |
| Pricing shape | Per query, plus per GiB indexed, plus grounding — three dimensions | One rate per search, whole |
| Data it searches | Your own documents, your site, or the open web, by configuration | Its own index of the open web, read continuously |
| Setup before the first answer | Configure a data store, index your corpus, tune the deployment | None — the index is already read |
| Searches your private documents | Yes, that is its central capability | No |
| Content structure | Configured per deployment | Filed as what it is — a judgment, a standard, a filing, with its identifier |
Swipe the table sideways to see both columns.
Google rates from its own pricing page for this product, read 8 September 2026: Search Standard Edition $1.50 per 1,000 queries, Search Enterprise Edition $4.00, Advanced Generative Answers a further $4.00 per 1,000, index storage about $5.00 per GiB per month, grounded generation on your own data $2.50 per 1,000 and grounding on Google Search $35.00 per 1,000, with 10,000 free queries per account per month. Google now lists the product as Agent Search on its Gemini Enterprise Agent Platform, formerly Vertex AI Search. askFinz rates as published on pricing.
What Vertex AI Search is
Vertex AI Search is an enterprise search and retrieval product built on Google's infrastructure, for companies that want to search their own documents, their website, or the open web with Google-grade relevance and grounding for generative answers. It is priced per query by edition, and then queries, indexed data volume and grounding calls each carry their own cost — standard for an enterprise platform, and honest, because indexing a private corpus at scale really is not the same cost as answering a question about it.
What askFinz is
askFinz runs its own crawled web index, read continuously rather than configured and rebuilt, so an answer is a lookup rather than a fetch that begins when you ask. On top of it sit a Search workspace, Research, Chat, Code and News, a browser extension and a desktop app — the same index and one sign-in, not a service each of your own applications has to call. A question returns the matched passage together with the answer, and the address it was read from, and what the index holds is filed by what each document actually is: a judgment, a standard, a filing or a clinical study comes back as that kind of record with its identifier attached. PDFs, Office files, ebooks and data files are converted to readable text and read, not merely linked to. askFinz does not sell index access as a standalone feed or API.
The thing Vertex does that askFinz does not
Your own documents. Vertex AI Search will index a private corpus, apply your access controls to it, and ground generative answers against it alongside the open web. askFinz answers from its own index of the web and does not index your document store. If the search you need spans internal material, this comparison is already over and Vertex is the answer.
What a flat rate actually changes
The query rate is published, but it is not the bill. The other side of Vertex's flexibility is that the cost of a deployment still depends on how much you bring and how heavily you ground: at $1.50 per 1,000 Standard queries the search itself is cheap, and a corpus held at about $5.00 per GiB per month plus $2.50 per 1,000 grounded generations is where the number actually moves. askFinz has no such variable: nothing to index, nothing to configure, nothing to ground separately — $0.75 to $3.50 per 1,000 searches, whole.
A component, or a place to work
One of these is a call you build against. The other is somewhere you open and use.
Choose Vertex AI Search if
- You need to search your own private documents. askFinz does not index them.
- You are already on Google Cloud and want search inside the same billing, identity and compliance perimeter.
- Enterprise procurement requires a vendor with formal support, SLAs and a compliance posture at that scale.
- You want to tune relevance, data stores and grounding behaviour per deployment.
- Your search needs to respect existing document-level permissions in your own corpus.
Choose askFinz if
- The search you need is of the open web, and the answer is what you are after.
- You want a price you can state in one sentence before you have modelled your own usage.
- You do not want to build and maintain an indexing configuration to get a first answer.
- You want the passage the answer came from, checkable, with the address it was read from, alongside the answer itself.
- You want web content filed by what it actually is — a judgment, a standard, a filing, with its identifier — rather than by how you configured a data store.
- You want search to be a place people work — a workspace, a browser extension and a desktop app on one sign-in — rather than a retrieval service your own applications have to be built against.
FAQ
Questions people ask
The things people actually ask before choosing between Google Vertex AI Search and askFinz.
5 questions · open one to read the answer
Google publishes $1.50 per 1,000 queries for Search Standard Edition and $4.00 for Search Enterprise Edition, read from its own pricing page on 8 September 2026, with the first 10,000 queries per account per month free. Those are not the whole cost: Advanced Generative Answers adds $4.00 per 1,000, index storage runs about $5.00 per GiB per month, grounded generation on your own retrieved data is $2.50 per 1,000 and grounding on Google Search is $35.00 per 1,000. Compare the query rate against askFinz's $0.75 top-up, $1.00 with the extension or a paid plan and $3.50 standalone — then remember that only one side has a corpus to store and ground.
No. It answers from its own index of the open web, already read and filed by document type. If internal material is what you need to search, Vertex is the right product and this page does not pretend otherwise.
No. There is no corpus to configure and nothing to index — the reading has already happened.
Neither side publishes a benchmark that would settle it, and none is invented here. Google's retrieval has run in production for years and operates at very large scale. askFinz retrieves against an index organised by document type, which is a different bet rather than a measured win.
No. askFinz does not sell index access as a standalone feed or API.
See how the index works, or read the fuller case for owning an index. Join the beta and try it against a real question.