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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.
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.
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.
Continuous data trust intelligence for DataHub. Audit. Propagate. Remediate.
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.
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.
A DataHub-grounded agent that checks real metadata and lineage before schema changes, then returns ALLOW, REVIEW or BLOCK with an evidence-backed migration plan.
Finds unmasked PII in your DataHub catalog, checks downstream lineage impact, and ships the fix as a GitHub PR — never as raw DDL. Closes the loop by writing governance state back to DataHub.
An autonomous agent using DataHub metadata context to detect untagged PII, generate masked dbt transformation models, and write governance tags & assertions back to the Context Graph.
DataHub agents can already write what they learn back to the catalog. Nothing ever takes it away. Half-Life expires agent memories when the schema, glossary or ownership beneath them changes.
Buyer and seller agents turn live evidence into safe software decisions, powered by CockroachDB and Amazon Bedrock.
A lie detector for data catalogs. Polygraph runs your pipeline, catches the lineage DataHub got wrong, and writes the verdicts back, where people and agents actually look.
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.
ContextBridge is an autonomous AI agent that uses DataHub context and institutional memory to investigate work, prevent repeated failures, discover experts, and take evidence-based action.
Smart Memory & Trust Ledger for DataHub: AI agents learn from past decisions, skip redundant scans, and build proven reliability.
DataGuard Agent transforms DataHub with AI by detecting governance risks, generating intelligent fixes and automating documentation and alerts—making enterprise data reliable, secure, and audit-ready.
Designed an AI agent to search the web using a given query by requesting the Tavily API to web search and take the response and formatting it using the Gemini model which gives a structured answer
A supply chain is a lineage graph. When a node fails, REROUTE maps the blast radius, finds the reroute, and writes the incident back to DataHub ,so the graph always tells the truth.
Three AI agents that find, fix, and verify data quality problems in your DataHub catalog — coordinating through the catalog itself, powered by a locally fine-tuned 7B model.
When data consent changes, RevokeGraph finds every affected model, orchestrates an approved replacement, and proves the withdrawn data no longer reaches production.
DataHub-grounded schema migration agent with deterministic policy, counterfactual dbt proof, immutable safety cases, and post-merge verification.
The DataHub MCP agent that compiles breaking warehouse DDL into a provable, owner-routed migration plan.
ASG-3 es un sistema multi-agente para gobernanza autónoma en DataHub. Aplica el ciclo MGR y consenso con veto de privacidad para asegurar metadatos auditables y seguros.
Hexacortex is a biomimetic AI agent using DataHub MCP to detect lineage/governance breaks. It generates repair code and writes the solution back to the graph.
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