An overview of Rig's six major categories of work
Rig replaces the stack you'd build to do all of this yourself. Use the whole thing or just the parts you need.
Ingestion
Pull data in from wherever it lives. Warehouse or no warehouse, your call.
- SaaS connectors for the tools your team already uses
- Direct warehouse sync (Snowflake, BigQuery, Databricks, Postgres)
- Real-time and scheduled pipelines
- Schema drift handled automatically
Context
The brain. What your data means, how it joins, what's PII. Auto-built.
- Context layer auto-generated from your data
- Semantic layer that embeds dbt SL or Cube if you have one
- Business terms and certified metrics in plain English
- PII detection out of the box
Connect
Turn an insight into an action. On a schedule or on a trigger.
- Builder agent for end-to-end workflows
- Gardener agent keeping your context layer current
- Scheduled and triggered runs
- Slack, CRM, and email actions out of the box
New
AI migration mapping
Map the estate from schema and real usage. Weeks, not months.
- Systems map across CRMs, ERPs, support tools, warehouses
- Drop candidates backed by evidence, not a black box
- Dry run before anything touches a live system
- Managed-service option with a human in the loop
Hosting & access
Run internal apps and AI workflows on Rig without exposing raw data.
- RBAC down to the row level
- PII sandbox for sensitive queries
- Audit trail and SOC 2 Type II (in progress)
- Internal app hosting with no devops
AI interface
Plug Rig into whatever AI tool your team is already using.
- Rig MCP server, ready for Claude, ChatGPT, Cursor, Codex
- Per-user permissions enforced through the AI tool
- Full audit of every AI query
- Custom agent SDK
See it on your data
Connect your warehouse or pick a few SaaS tools. Rig builds a context layer you can actually use.