AI & Models · Integration
AWS Bedrock
Add AWS Bedrock to your product for your customers, and give your AI agents governed access to it.
Embed an AWS Bedrock integration so your customers can run foundation models through their own AWS account from inside your product, with usage attributed per tenant and every call logged. fastn handles each customer's credentials and API upkeep, so model access is configuration rather than a service you operate on their behalf.
In your product
Embedded for your customers. Per-tenant auth, no per-customer code, maintained by fastn.
Invoke models using each customer's own AWS account, so their usage bills to them.
Let customers choose which model and region their data is processed in.
Read available models so your product only offers what a customer can actually use.
Batch or stream responses depending on what your product needs.
For your AI agents
Governed, audited access for the agents you build, through the MCP server.
An agent calls a model through the customer's own account rather than a shared one.
An agent selects a model appropriate to the task within governed permissions.
An agent chains a model call into a longer workflow with each step audited.
Example prompt
Summarise these support tickets using the customer's configured model and return the top three themes.
Set up AWS Bedrock in 4 steps
- 01Open the AWS Bedrock connector from your fastn dashboard.
- 02Have each customer authenticate their AWS account with least-privilege scopes.
- 03Choose the models and regions your product offers, then enable the actions you need.
- 04Call them from your product, or expose them to an agent through the MCP server.
Why teams use the AWS Bedrock integration
What you get by embedding it with fastn instead of building it yourself.
- Ship an AWS Bedrock integration without building it. Your customers connect their own AWS Bedrock 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 an AWS Bedrock update is not your on-call problem.
- One integration serves your product and your agents. The same governed AWS Bedrock 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.
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AWS Bedrock integration FAQ
How do I add an AWS Bedrock integration to my product?
Enable the AWS Bedrock connector in your fastn dashboard, then let each customer authenticate their own AWS Bedrock account. fastn handles the OAuth flow, token storage and refresh per tenant, so there is no AWS Bedrock client code in your app and no per-customer branch in your codebase. Setup is 4 steps.
Do my customers each connect their own AWS Bedrock account?
Yes. Every connection is scoped to the individual customer, so each authorises their own AWS Bedrock 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 AWS Bedrock 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 calls a model through the customer's own account rather than a shared one.
Who maintains the AWS Bedrock integration?
fastn does. When AWS Bedrock 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 AWS Bedrock API key and quota does each call use?
Each customer authorises their own AWS Bedrock 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 AWS Bedrock integration?
A common starting point: invoke models using each customer's own AWS account, so their usage bills to them. 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 AWS Bedrock integration cost?
It is included. Pricing is based on connected accounts, not on how many connectors you enable, so adding AWS Bedrock does not change your per-connector cost. You can start free with 3 connected accounts.
Add AWS Bedrock to your product
Start free with 3 connected accounts. No sales call required, and no per-customer integration code.