Features
What your team and your agents can use in Rig
Rig gives people and AI agents the same definitions and the same permissions, in Rig and in the AI tools your team already uses. Each feature below links to a guide that shows how it works.
Business context
Context Studio
Curate the definitions, joins and rules behind every answer.
Read the guideSemantic layer
Generate metrics from scratch, or import them from LookML and other tools.
Read the guideUsage rules
Write down your team’s definitions and edge cases so Rig answers questions your way.
Read the guideGold star
Mark the tables your data team endorses.
Read the guideContext quality
See a score for your context, work through the biggest gaps first and grade real answers in the Eval Lab.
Read the guideAgents and access
Rig MCP
Connect Claude, Claude Code, Cursor, Codex or ChatGPT to your data with governed access.
Read the guideAgent roles
Each agent gets its own role, token and daily call limit, and every call it makes lands in a named audit trail.
Read the guideAccess control
Set schema, column and PII permissions, then preview the SQL before you ship a change.
Read the guideAutomations
Turn a recurring question into a scheduled agent, built in Claude or in Rig.
Read the guideData apps
Data apps
Open, run and share apps, and use the Inspector to trace any number on the screen back to the exact query that produced it.
Read the guideApp state
Apps remember flags, notes and saved views.
Read the guideVirtual data models
Summarise every sales call, ticket or transcript into one table your team can query.
Read the guideMissions
Fill gaps in your CRM as a team: Rig proposes matches and an admin approves the writeback.
Read the guideEmbed in Salesforce
Show a Rig app inside Salesforce, and each viewer sees only what their Rig permissions allow.
Read the guideTalk to Rig
What work do you want to improve?
Tell us where your team spends time, loses money or needs better information.
In a 30-minute call, we’ll discuss the data and systems work that could help.