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An embeddable approval gate where agents and tools propose DataHub changes, PDX verifies, then MCP write-back only after approval.
AI agent that reads DataHub lineage, evaluates risk using governance tags, and autonomously raises incidents to halt downstream pipelines before corrupted data spreads.
An agent that reads your schema change, walks DataHub's lineage, and tells you exactly what breaks, how sure it is, and how to ship it safely.
Cinematic Context Platform: AI agent giving video pipelines full DataHub context (lineage, MCP server, autonomous orchestration)
DataHub shows you the blast radius. LineagePilot closes it — reasoning, fixing, and reviewing schema changes before they break production.
DataHub-grounded RAG agent that turns plain-English data questions into trusted metadata insights, lineage-aware recommendations, and SQL-ready artifacts with citations.
An autonomous agent that investigates your catalog's "cold cases" — undocumented, unowned tables — by cross-referencing schemas, lineage & real SQL queries, then writes the knowledge into the graph.
An AI agent that uses DataHub context to assess the blast radius of data changes, require human approval for risky actions, and write auditable decisions back to the metadata graph.
AI Financial Operating System for the next generation of personal finance.
Compile the forget request—don't guess it. DataHub-grounded remediation planner: lineage → reviewable plan → sandbox SQL → catalog writeback.
DataHub-native evidence verification with inherited lineage, ownership, schema context, and auditable write-back.
obsel tracks a right-to-erasure request across systems it cannot see: each asset reached stays unattested until someone who can look signs for it. The same lineage flags stale agent work.
An AI governance agent that reads DataHub's lineage graph and catches silent data drift before a human ever has to.
Pathfinder is an automatic safety check that runs the moment a change is proposed. It plugs into two things teams already use: GitHub (where engineers propose changes) and DataHub
AI agents trace wrongful claim denials to their root cause through DataHub's lineage graph — then fix them.
AI agent that detects schema changes, broken lineage, and production ML risks using DataHub and recommends fixes before failures happen
Graph-linked Decision Provenance for DataHub — replayable, reusable, and self-invalidating reasoning behind high-stakes data changes.
Turn DataHub failures into grounded, reviewable repairs with sealed approval and verified write-back.
An evidence-backed agent that stops breaking warehouse changes before merge.
A multi-agent AI team that reads DataHub over MCP, finds governance risks (failing checks, untagged PII, blast radius), writes approval-gated fixes back, and verifies them.
A DataHub-powered agent that maps downstream impact, scores schema-change risk, identifies required approvals, and generates migration safeguards before merge.
Reviews data pull requests against DataHub's metadata graph, scores breaking schema changes deterministically, and writes the finding back so the next agent inherits it.
What breaks if this ships? Blast Radar walks your DataHub lineage over MCP, ranks which downstream assets a change actually endangers, and writes the verdict back into the graph.
Check AI-written data code against your catalog before it merges. The checker does not contain a model.
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