A table just broke.
Ripple already knows what's on fire.
Ripple is an AI agent for DataHub. It traces the downstream blast radius of a broken asset, ranks the impact by severity, and writes the incident back into the catalog — so the next engineer inherits the answer.
Try it — simulate an incident
Click any table to break it. Ripple's logic runs right here in your browser — no install, no DataHub — tracing the blast radius, ranking severity, and writing the incident back.
Not just a query tool — an agent that acts
Ripple reads lineage, reasons about impact, and writes the incident back to DataHub. Everything below works end-to-end.
Downstream blast radius
Trace every affected table and dashboard across all lineage hops, ranked by criticality with an auto-assigned SEV level.
Upstream analysis
Flip the direction: trace upstream to rank the likely sources of bad data, closest raw tables first.
Column-level lineage
Not just "this dashboard" — the exact column that traces back to the broken field.
Auto-trigger watch
Poll for broken assets and triage them automatically — no human in the loop to kick it off.
Native incidents
Applies an incident tag, saves a runbook, and raises a first-class DataHub Incident entity on the asset.
Web + terminal
A rich CLI and a read-only web dashboard with an interactive lineage graph and light/dark themes.
How it works
One command: read the lineage, reason about impact, write the incident back.
Read
Traverse downstream lineage across every hop and platform via the DataHub MCP Server — Snowflake, dbt, Looker, PowerBI, Tableau.
Reason
Rank the blast radius by criticality and assign a severity. Facts are gathered by code; only the narrative is written by an LLM — so the analysis stays trustworthy.
Write
✓ incident tag
✓ runbook document
✓ native Incident entity
Persisted back so the next engineer inherits full context.
Run it in one command
Works against any DataHub instance — a local quickstart is enough.