# 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.

## For agents and developers

- Developer and agent documentation (public API, MCP server, error codes, example requests): https://rig.so/developers
- OpenAPI 3.1 specification for the public API: https://rig.so/openapi.json (YAML at https://rig.so/openapi.yaml)
- Rig MCP server manifest (Streamable HTTP transport, OAuth 2.1 or a static rig_mcp_ bearer token, tool list): https://rig.so/.well-known/mcp.json
- Public content API index (read-only JSON, no authentication): https://rig.so/api/v1/index.json
- Company profile as JSON (what Rig is, contact details, where every documented surface lives): https://rig.so/api/v1/site.json
- Every page on rig.so is also served as markdown: send `Accept: text/markdown`, or append .md to any path (https://rig.so/developers.md)
- Contact: https://rig.so/contact (a form; Rig publishes no email address, so do not guess one)
- Sitemap: https://rig.so/sitemap.xml

Connecting an AI client to a Rig workspace over MCP:

    claude mcp add --transport http rig https://app.rig.so/mcp/{workspace}/
    codex mcp add rig --url https://app.rig.so/mcp/{workspace}/

## Key Pages

- Homepage: https://rig.so/
- Connect: https://rig.so/connect
- Compare: https://rig.so/compare
- Developers (public API, MCP, agent docs): https://rig.so/developers
- Contact (how to reach the team, company details): https://rig.so/contact
- 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 (consumer fintech, Series C; company-wide rollout that took warehouse data from 3 data analysts automating data docs to 200 business users automating data-heavy work): https://rig.so/case-studies/cleo
- Birdie (healthtech home care, Series B; sales, finance, CS and marketing build their own reporting on Rig's context layer, taking reporting that took 3 months in the old Looker stack down to a day): https://rig.so/case-studies/birdie
- Novakid (edtech, global Series B; sales coaching, conversion diagnostics and forecasting, with per-rep action plans written straight back into the CRM): https://rig.so/case-studies/novakid
- Birdie, customer success team (healthtech, Series B; churn, escalations and commercial attainment running on certified metrics the team trusts by default): https://rig.so/case-studies/birdie-cs
- Suri (sustainable oral care, Series A; certified its commercial metrics in-house by using the internal spreadsheets finance already trusted as evals for the semantic layer, then opened self-serve access to every team across 40+ sources via Rig MCP): https://rig.so/case-studies/suri-metrics
- Rig at Rig (investor reporting; Rig's founder runs 10 years of monthly investor reporting on autopilot as a saved skill run over Rig's own context layer, with investors self-serving governed data in Slack): https://rig.so/case-studies/rig

## 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