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Healthcare Sentinel is an AI agent that triages healthcare data quality like a clinician — discovers issues in DataHub, explains patient harm, remediates with approval, and learns across runs.
DataHubX is a governance layer for AI agents acting on DataHub. Every change is approved against live data and re-verified at execution — if the data changed since approval, the action is blocked.
Autonomous incident commander for DataHub: triage, diagnose, patch, impact-map, and write-back — one command, end to end.
CMG catches silent AI failures in hospitals using DataHub's live data lineage to flag risky pipeline changes in real time, before a model quietly starts giving wrong answers, saving lives of millions.
Catch silent ML failures before production. Traces DataHub lineage from training data → features → models → deploy, blocks risky releases, and writes risk evidence back to the catalog.
Autonomous AI agent that detects upstream schema drift & storage waste, generates validated code patches, opens PRs, and writes governance state back to DataHub — end-to-end.
DNASeed is an AI-powered molecular data preservation platform using DataHub context and governance to intelligently archive, verify, and recover datasets as Digital DNA Seeds.
Relay gives every AI assistant lineage-aware decision memory, catching conflicting changes before they ship.
DataHub X OpenTelemetry. A green AI run can still be wrong. DataHub explains the data. Replay checks the answer. OpenTelemetry proves what happened. Themis decides if the release can move.
An autonomous agentic AI system that identifies which columns should be classified as PII by tracing schema, existing tags/glossary, lineage, sample values, and masking status across a data pipeline.
Ten agents over a time machine for DataHub's context graph. Reconstruct what the catalog said at any past instant, replay any agent decision against it, and prove if agent or the metadata was wrong.
Someone says a metric means one thing on Slack. Your data docs say another. Cert Sync catches the disagreement, gets it settled, and keeps every AI agent on the same page.
Your coding agent can ship. Model Canary can say absolutely not.
Schema changes break pipelines silently. DataGuard AI reads the pull request, traces the blast radius through DataHub lineage, and ships the fix as a reviewable PR.
Aegis uses DataHub’s context graph to detect data risks, trace downstream impact, and keep AI-driven changes safe, compliant, and explainable.
Scoped, revocable context cards that gate what AI agents can see and do inside your DataHub catalog
An AI steward agent cleans Radio Milwaukee's hand-typed playout logs, governedend-to-end in DataHub, and turns them into a music discovery graph where everyconnection shows its receipt.
iGraph turns DataHub lineage into an Impact Graph, seals each proposed change in a signed Impact Pact, and enforces it before an autonomous agent can execute.
The Context Layer for Consistent AI Personas
AI chat assistant that answers questions about datasets, columns, and lineage by reading live metadata from your DataHub instance.
Sentinel AI stops breaking data schema changes before merge by using DataHub MCP context to assess blast radius, block risky PRs, generate safe fixes, and preserve decisions.
Autonomous anomaly detection agent that monitors data pipelines, queries DataHub MCP Server for lineage context, identifies root causes, and generates actionable incident reports.
An agent that reads your real DataHub schema before writing SQL and then proves it did.
DataHub knows your owners, PII tags and freshness. It has no opinion. mlgate is that opinion: it gates ML releases on lineage and writes the verdict back.
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