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A metadata-aware migration & impact-analysis agent that generates production-safe schema changes and closes the loop by writing verified impact data back into DataHub.
Discovers your AI agent fleet, detects poisoned MCP tool descriptions, and governs it all in DataHub.
An autonomous AI data guardian that uses DataHub and MCP to detect data-quality risks, investigate root causes, and explain business impact.
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.
Your closet as governed data in DataHub. An AI roasts your wear habits using only verified stats. No cap.
Generate trusted SQL. Detect schema drift. Repair broken queries automatically. DataHub Aegis keeps analytics reliable as enterprise data evolves.
DataHub can tell you a table is cold. It cannot tell you that half a table is cold — and it cannot move a single byte. ColdLineage does both and writes the receipt back into DataHub.
Mama said, life’s like a box of chocolates. STOP! You do know DataHub labeled it underneath, don't you?
**«ما مرزِ میانِ فیزیک و دیجیتال نیستیم؛ ما خودِ آن «مرز» هستیم. ما نقطهیِ تلاقیِ ماده و معنا هستیم. ما دو جهانِ جدا نیستیم؛ ما یک «واقعیتِ واحد» هستیم که از دو لایهیِ مختلف ساخته شده است.»**
LATCH turns an external AI-training dataset transfer into a governed release: DataHub context, BigQuery proof, human approval, safer output, and a verifiable passport.
Keystone ranks your data estate by what would hurt most if it broke — so a team with time to protect one thing protects the right one.
Autonomous Metadata Context & Governance Engine for Production AI Agents, integrated with DataHub
Autonomous SRE agent powered by DataHub MCP & GitHub Actions that detects breaking schema changes in PRs, traces column lineage, and auto-generates dbt fixes.
Undertow blocks ML deploys when upstream data breaks — traces it, names the engineer, stops CI.
It is an AI data-change intelligence agent that uses DataHub context and lineage to predict a change’s blast radius, identify what could break, and generate a safe rollout plan before production.
An AI-powered data engineer that understands metadata, diagnoses data issues, and automates reliable data workflows.
Ant WMS, an AI-powered warehouse management system built to solve vendor data chaos, reactive slotting, and siloed reasoning.
Evidence-led safety for analytics schema changes before merge.
An agent that finds the silent failures in your dbt warehouse — green build, green tests, wrong revenue — proves them empirically, and hardens against them.
Scoped, revocable context cards that gate what AI agents can see and do inside your DataHub catalog
Blocks schema changes that break ML models. It asks DataHub which feature dies with the column, how much the model actually used it, and turns that answer into a failing CI check.
DataHub knows what your data is. Lore knows why.
An agent that reads your real DataHub schema before writing SQL and then proves it did.
Stale documentation can't hide. docFreshness flags an AI agent's context as stale the moment an upstream table it depends on drifts — and tells the agent exactly what changed and how to fix it.
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