Data and analytics agents

Agents that work on your data, grounded in business context.

Every company with 30+ people needs an internal data agent. OpenAI, Vercel, Uber, LinkedIn, and Salesforce are each building one.

The key themes are: ground the model in curated context, let it self-correct, enforce hard boundaries on writes.

Learn How To

Concern	Page
Run SQL and cite it	Querying your data
Ground answers in business context	Grounding in context
Stop repeating mistakes	Self-correcting agents
Read-only vs read-write boundaries	Safe data access
Turn repeat questions into views	Materialization
Put it behind your surfaces	Serve and embed

Explore

Querying your data

SQL tools, schema introspection, and answers that cite the query.

Grounding in context

Validated queries, table metadata, and business rules per question.

Self-correcting agents

Errors become learnings. The same mistake cannot recur.

Safe data access

Read-only and write boundaries enforced by the engine.

Materialization

Repeat questions become reusable views.

Developer Resources

• Learning Machines
• Dash tutorial
• Serve as an API