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.Documentation Index
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| 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 |
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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.