Use internal data in your AI tools
We built Rig to give AI tools the business context they need, so every team can get accurate answers from company data, in the tools they already use.
Every team has questions but when a question falls outside an existing dashboard, the answer often becomes a request to the data team.
Toby Mather
Running the product team at my previous company, I'd wait for dashboards. When Claude came along, it couldn't understand our complex internal data. It needed a good map of our data to understand how our business worked.
Jakub Langr
At Palantir, we built the ontology for major enterprises by manually constructing complex maps of their internal data. In the agent era, those maps should build and maintain themselves.
Why we built Rig
Don't give AI access to raw data. Give it context.
AI doesn't understand your data, how it connects, and who should have access to it. Rig gives it a trusted map of your definitions, relationships, permissions, caveats, and business logic so answers are grounded in how your business actually works.
Context should update as the business changes
Business context shouldn't be manually rebuilt every time the underlying data changes. Rig keeps your context layer current, so teams and tools get up-to-date answers without constant manual maintenance.
Action over dashboards
The people closest to revenue, retention, spend, and growth should be able to ask, decide, and act — without turning every new question into a data-team ticket.