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Stop Code Slop, put your agent on a leash and know where your code is going.
Autonomous data incident response that investigates, explains, and learns.
GCIA turns DataHub metadata changes into human-gated, evidence-backed actions by mapping downstream impact, revalidating risk, and proving outcomes without blind retries.
An autonomous AI Data Reliability Engineer that monitors, investigates, and remediates data quality and governance issues across modern data platform
A two-phase offboarding agent for data engineers
AI cleanup agent that scans your DataHub context graph, flags orphaned, undocumented, and broken-lineage datasets, then writes LLM-generated fixes back to the graph.
An autonomous data steward for DataHub. It investigates broken data, retires dead tables, and writes every finding back into the catalogue; so the next person inherits instead of repeating the work.
An agent that answers hard questions about your DataHub catalog - lineage, ownership, PII, blast radius - shows every catalog call behind the answer, and writes what it learned back into DataHub.
Production ML Agent built on DataHub's end-to-end graph lineage to protect ML models from silent upstream pipeline data mutations
AI decision copilot for food & plant products entering China — combining official market-access requirements, China Customs data and governed evidence into clear, traceable decisions and actions.
AI agent that reads real DataHub metadata (schema, lineage, glossary) and generates runnable dbt models + Airflow DAGs, writing results back to DataHub lineage.
MetaGate turns DataHub metadata into an allow-or-block decision before an AI agent acts.
Axiomatic Intelligence for data incidents: DataHub-powered agents prove which branch is unsafe and preserve what can safely keep running.
Engineering begins with understanding. MetaLoom AI leverages real metadata, multi-agent reasoning, and auditable validation to generate code developers can deploy with confidence.
Chaos engineering for your data stack. BLACKOUT uses DataHub to simulate failures before production, map blast radius, find structural SPOFs, and turn every test into resilience memory.
Plan Your Meals, Simplify Your Cooking!
DHCP gives governance evidence an address. It maps DataHub metadata to evidence for AICM, GDPR, HIPAA, ISO 27001/42001, and SOC 2, then safely writes approved context back without grading compliance.
How many upstream feeds must break at once before your model notices? Sentinel Mesh computes that number from DataHub lineage, monitors it over time, and writes it back to the catalog.
Protect the scientific decision, not just the data pipeline. SciGuard detects silent drift, proves exact impact with DataHub lineage, contains selectively, and ships a proof-carrying repair.
Turn governed company metadata into decisions people can verify, approve, and remember.
An agent that reads DataHub via MCP, confirms real schema, flags stale Etsy listings, gets human approval, rewrites via a real multi-agent pipeline, then writes results back — closing the loop.
A DataHub-grounded agent that reviews risky data changes, generates safe patches, verifies them, and writes decisions back.
ContextGuard uses DataHub lineage to detect schema changes that threaten ML models, block risky PRs, and suggest safe fixes.
Self-healing data pipelines: AI agents that diagnose, fix, and document incidents using DataHub's MCP Server.
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