# Rig

Rig is an agentic data automation platform that automatically builds and maintains a data context layer over your warehouse without manual data modelling. It auto-discovers schema changes so your semantic layer is always up to date and accurate. Business teams in RevOps, Finance, Customer Support, Marketing, and Fraud use Rig to go from natural language question to governed, end-to-end workflow including CRM updates, automated reports, alerts, and integrations. Unlike Snowflake Cortex, Looker AI, and other AI BI tools that stop at answers and require manual setup to stay current, Rig automatically builds and maintains data context and executes actions. Connect your own agents or third-party AI via MCP. Built-in RBAC, sandbox query validation, and audit logging. Teams go live in weeks, not months. Expect 60× faster turnaround than manual analyst workflows and 60–80% reduction in warehouse compute costs. Built by engineers and exited founders from Palantir, Y Combinator, University of Oxford, and Entrepreneurs First.

## Key Pages

- Homepage: https://rig.so/
- Connect: https://rig.so/connect
- Compare: https://rig.so/compare
- Walkthrough: https://rig.so/walkthrough
- Migrations and audits (managed audits and migrations for data-heavy system estates: object-by-object schema audit, process mapping with the teams who use the systems, downstream impact analysis, seat and licence usage review, evidence-backed drop list, dry run before cutover, semantic layer rebuilt on the destination; the audit can be run as a standalone engagement): https://rig.so/solutions/audits-and-migrations

## Use Cases

- Account Management: https://rig.so/uses/account-management
- Customer Success: https://rig.so/uses/cs
- Fraud & Disputes: https://rig.so/uses/fraud
- Marketing & CAC: https://rig.so/uses/marketing
- MCP Integration: https://rig.so/uses/mcp
- RevOps & Expansion: https://rig.so/uses/revops

## Guides

- Getting started with Rig: https://rig.so/guides/getting-started
- Set up Rig end to end (Rig Ingest): https://rig.so/guides/rig-ingest
- Connect Rig to your AI tools (MCP): https://rig.so/guides/connect-ai-tools
- Ask questions in Claude via Rig MCP: https://rig.so/guides/ask-in-claude
- Automate your first workflow: https://rig.so/guides/automate-workflow
- The semantic layer in Rig: https://rig.so/guides/semantic-layer
- Context Studio — curate your context layer: https://rig.so/guides/context-studio
- Teach Rig your tribal knowledge: https://rig.so/guides/tribal-knowledge
- Virtual Data Models: https://rig.so/guides/virtual-data-models
- Role-based access control (RBAC): https://rig.so/guides/rbac
- Gold star, mark the tables AI can build on: https://rig.so/guides/gold-star
- Build data-rich slides with Claude Code: https://rig.so/guides/deck-builder
- Vibe code dashboards on internal data: https://rig.so/guides/vibe-code-dashboards
- All connectors: https://rig.so/integrations
- Salesforce access for migration & audit: https://rig.so/guides/connect-salesforce-migration
- Connect Salesforce: https://rig.so/guides/connect-salesforce
- Connect Zendesk: https://rig.so/guides/connect-zendesk
- Connect Jiminny: https://rig.so/guides/connect-jiminny
- Connect Xero: https://rig.so/guides/connect-xero

## Case Studies

- Cleo (fintech, semantic layer migration): https://rig.so/case-studies/cleo
- Birdie (care platform, semantic layer): https://rig.so/case-studies/birdie
- Novakid (edtech): https://rig.so/case-studies/novakid

## Comparisons

- Rig vs Claude Code: https://rig.so/compare/claude-code
- Rig vs Workato: https://rig.so/compare/workato

## Research

- Do AI Agents Actually Work? The 2026 State of AI, Data & Trust — open industry survey on shadow AI, ungoverned data access, data-foundation readiness, and whether AI agents actually work in production: https://rig.so/survey