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Silent schema drift breaks ML models without a crash. This 5-agent LangGraph team catches it, traces DataHub lineage, and writes the incident back to DataHub.
Know the downstream blast radius of schema changes before you merge.
Verify what an AI agent claims about your data — zero verdicts decided by a model — and publish each verdict back into DataHub, so the next agent inherits it from the catalog, not from Attest.
ZephyrAQ turns Hanoi’s fragmented air-quality data into evidence-backed source investigations and human-approved actions, enabling faster responses to pollution.
An AI agent that uses DataHub’s metadata graph to analyze schema changes, identify affected pipelines and ML models, generate safe fixes, and write results back to DataHub.
The evidence-backed ML lineage archaeologist for DataHub that turns historical incident patterns into proactive risk prevention.
See the metadata break, measure its blast radius, and repair it with proof.
Before you merge a column rename, Premortem scores which DataHub consumers break and how, and writes the forecast back to the catalog — before a dashboard tells the business
An agent that decides from DataHub context and can prove which version of that context justified each decision — and refuses to certify when it can't.
An autonomous AI incident commander that detects, investigates, and fixes data pipeline failures end-to-end — opening the PR, notifying Slack, and logging every step, without waiting for a human.
Know what ML breaks before you merge. Blastradar traces a data PR's changed columns through DataHub lineage to the ML models they'd silently break, and comments on the PR before it lands.
An AI agent that connects to DataHub, understands your organization's schemas, lineage, ownership, datasets, pipelines, and ML models, detects problems, explains their impact, and executes fixes.
An AI agent that turns data goals into contextual investigation paths — powered by DataHub.
An autonomous AI data engineer powered by DataHub that investigates pipeline failures, explains root causes, generates production-ready fixes, and captures organizational knowledge.
Before you drop a column, Blast Radius uses DataHub's indexed SQL to prove what breaks, generate reviewable patches, and identify the owners who need to act.
Mission control for production ML on DataHub lineage
Agent that walks DataHub lineage graphs to catch schema drift & PII exposure before they break production ML models.
A DataHub-powered agent that maps downstream impact, scores schema-change risk, identifies required approvals, and generates migration safeguards before merge.
RegLens reads a bank's DataHub graph to find what a new regulation touches, costs acting now vs deferring vs minimum compliance, and writes the decision back so the next team inherits it.
An AI agent that scans entire MongoDB collections to discover hidden schema blind spots DataHub misses — then writes enriched metadata back to the catalog.
The DataHub-powered agent that blocks dangerous dbt changes, proves a real repair, gates release on owner approval, and writes reusable knowledge back to DataHub.
Close the schema-change loop with DataHub-grounded impact, action, and memory.
An AI agent that reads DataHub's MCP Server to catch AI agents violating data-access policy — then writes the violation straight back to DataHub and opens a GitHub issue automatically.
Metadata-aware code generation grounded in DataHub. ContextForge analyzes schema, lineage, ownership, governance, and usage before generating impact-aware data code, tests, and review evidence.
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