Data & Storage · Integration
Sigma Computing
Add Sigma Computing to your product for your customers, and give your AI agents governed access to it.
Sigma Computing puts a spreadsheet interface over the warehouse without copying anything out of it, so a query your product triggers runs on the customer's own Snowflake, BigQuery or Databricks, under their credentials and against their spend. An embedded Sigma integration reads workbooks and the elements inside them, exports or downloads query results, reads the data models and connections an organisation has defined, and adds or deactivates members. The architecture has a consequence worth designing around: Sigma is not a copy of the data, so a slow read is a warehouse question, and what a connection can reach is bounded by the warehouse grant behind it as well as by Sigma's own permissions. fastn keeps each organisation's client credentials per tenant and follows the API.
In your product
Embedded for your customers. Per-tenant auth, no per-customer code, maintained by fastn.
Let each customer connect their own Sigma organisation so your product pulls results from the workbooks their analysts already maintain.
Export a workbook element as data so your product uses the number that customer's team defined rather than one you recomputed.
Read the data models and connections available to a customer so your setup screens offer their real options.
Add or deactivate members from your product so access to shared analysis follows your own user list.
For your AI agents
Governed, audited access for the agents you build, through the MCP server.
An agent reads the result of an existing workbook query instead of inventing SQL of its own.
An agent explains where a figure comes from by reading the data model behind the workbook.
An agent exports a result set for a report within scoped permissions, with the request logged per tenant.
Example prompt
Pull the latest figures from this Sigma workbook and tell me which segment moved most since last month.
Set up Sigma Computing in 4 steps
- 01Enable the Sigma Computing connector in your fastn dashboard.
- 02Have each customer generate client credentials in their own Sigma organisation so calls run under their access.
- 03Choose the workbooks and elements your product reads, map the columns you need, then enable the actions you want.
- 04Call it from your product and expose the same connection to your agents through the MCP gateway.
Why teams use the Sigma Computing integration
What you get by embedding it with fastn instead of building it yourself.
- Ship a Sigma Computing integration without building it. Your customers connect their own Sigma Computing account inside your product and work their records, datasets and fields there, with no per-customer code on your side.
- Handle the part that actually costs time: schemas differ per customer and change without notice, and volumes can be large. fastn owns the auth, token refresh, rate limits, pagination and breaking-change fixes, so a Sigma Computing update is not your on-call problem.
- One integration serves your product and your agents. The same governed Sigma Computing connection powers in-product features and gives AI agents scoped, audited access, so you read and write your customers' data where it already lives without wiring it twice.
Used by these teams
Compare with
Snowflake
Databricks
LookerOften used alongside
Tools the same teams tend to run next to Sigma Computing, across other categories.
Anthropic Claude
OpenAI
Azure OpenAI
Hugging FaceSigma Computing integration FAQ
How do I add a Sigma Computing integration to my product?
Enable the Sigma Computing connector in your fastn dashboard, then let each customer authenticate their own Sigma Computing account. fastn handles the OAuth flow, token storage and refresh per tenant, so there is no Sigma Computing client code in your app and no per-customer branch in your codebase. Setup is 4 steps.
Do my customers each connect their own Sigma Computing account?
Yes. Every connection is scoped to the individual customer, so each authorises their own Sigma Computing account and only ever sees their own records, datasets and fields. 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 Sigma Computing 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 reads the result of an existing workbook query instead of inventing SQL of its own.
Who maintains the Sigma Computing integration?
fastn does. When Sigma Computing 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.
Does the Sigma Computing integration adapt when a customer's schema changes?
Schema and field mapping is configuration per customer, so a change on their side is a mapping update rather than a code change and a release on yours.
How are large Sigma Computing reads handled?
Pagination and throttling are handled for you, and initial backfills are rate-limited so a large import does not exhaust a customer's API allowance.
What can I build with the Sigma Computing integration?
A common starting point: let each customer connect their own Sigma organisation so your product pulls results from the workbooks their analysts already maintain. 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 Sigma Computing integration cost?
It is included. Pricing is based on connected accounts, not on how many connectors you enable, so adding Sigma Computing does not change your per-connector cost. You can start free with 3 connected accounts.
Add Sigma Computing to your product
Start free with 3 connected accounts. No sales call required, and no per-customer integration code.