AI & Models · Integration
Google Document AI
Add Google Document AI to your product for your customers, and give your AI agents governed access to it.
Embed a Google Document AI integration so your customers can turn the documents they hand your product into structured data using their own Google Cloud credentials and their own processors. Extraction runs per tenant, so usage sits with the customer who caused it, and every request is logged so an extracted value can be traced back to the document and processor that produced it. fastn handles credential storage, long-running requests, and API upkeep.
In your product
Embedded for your customers. Per-tenant auth, no per-customer code, maintained by fastn.
Let customers extract fields from uploaded documents in your product using their own processors.
Read the confidence attached to each extracted field so your product can route low-confidence results to a human.
Process documents in batches so a bulk import does not block the user interface.
Trigger the next step in your product when extraction finishes.
For your AI agents
Governed, audited access for the agents you build, through the MCP server.
An agent extracts the fields it needs from a document before acting on them.
An agent checks extraction confidence and asks for human review rather than guessing.
An agent reacts to a finished extraction and writes the values into the right record within governed permissions.
Example prompt
Extract the fields from this batch of invoices and list any where a value came back below 80 percent confidence.
Set up Google Document AI in 4 steps
- 01Open the Google Document AI connector from your fastn dashboard.
- 02Have each customer authenticate their own Google Cloud project with least-privilege scopes.
- 03Select the processors and map the extracted fields your product uses, then enable actions and triggers.
- 04Call them from your product, or expose them to an agent through the MCP server.
Why teams use the Google Document AI integration
What you get by embedding it with fastn instead of building it yourself.
- Ship a Google Document AI integration without building it. Your customers connect their own Google Document AI account inside your product and work their models, requests and outputs there, with no per-customer code on your side.
- Handle the part that actually costs time: per-customer keys, quotas and cost attribution matter more than schema here, because every call is billed. fastn owns the auth, token refresh, rate limits, pagination and breaking-change fixes, so a Google Document AI update is not your on-call problem.
- One integration serves your product and your agents. The same governed Google Document AI connection powers in-product features and gives AI agents scoped, audited access, so you give your product and your agents a model call each customer pays for themselves without wiring it twice.
Used by these teams
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AmplitudeGoogle Document AI integration FAQ
How do I add a Google Document AI integration to my product?
Enable the Google Document AI connector in your fastn dashboard, then let each customer authenticate their own Google Document AI account. fastn handles the OAuth flow, token storage and refresh per tenant, so there is no Google Document AI client code in your app and no per-customer branch in your codebase. Setup is 4 steps.
Do my customers each connect their own Google Document AI account?
Yes. Every connection is scoped to the individual customer, so each authorises their own Google Document AI account and only ever sees their own models, requests and outputs. That per-tenant isolation is the point of an embedded integration: you support the long tail of customer setups without maintaining an integration per customer.
Can AI agents use this Google Document AI integration?
Yes. The same connection is exposed to your agents through the fastn MCP gateway, with permissions scoped per tenant and every call audited. An agent extracts the fields it needs from a document before acting on them.
Who maintains the Google Document AI integration?
fastn does. When Google Document AI changes an endpoint, deprecates a field or alters its auth, the fix lands in the connector rather than in your backlog, and your customers' connections keep working.
Whose Google Document AI API key and quota does each call use?
Each customer authorises their own Google Document AI account, so usage, rate limits and cost land on the customer that caused them. You are not metering a shared key and re-billing it, and one heavy customer cannot exhaust another's quota.
Are inputs and outputs auditable?
Yes. Every call is logged per tenant with the call, the input and the result, so an output can be traced back to what produced it. That matters more here than in most integrations, because a generated answer or an extracted field cannot be reconstructed from the request alone.
What can I build with the Google Document AI integration?
A common starting point: extract fields from uploaded documents in your product using their own processors. Teams also use it for the other use cases listed above, and expose it to agents for governed reads and writes.
How much does the Google Document AI integration cost?
It is included. Pricing is based on connected accounts, not on how many connectors you enable, so adding Google Document AI does not change your per-connector cost. You can start free with 3 connected accounts.
Add Google Document AI to your product
Start free with 3 connected accounts. No sales call required, and no per-customer integration code.