Disconnected Data Ecosystem
Multiple systems operate without unified governance.
Three integrated layers — foundation, interface, engine. Each one shown the way we actually pitch it: the problem, what we do about it, and how you check that it worked.
Data catalog, business glossary, stewardship workflows and automated lineage across 170+ connectors.
Explore data governanceMultiple systems operate without unified governance.
Discover, catalog and govern enterprise metadata.
Reliable data ready for analytics.
Omnichannel AI across Telegram, WhatsApp, web, mobile and email — five channels, three languages, one policy.
Explore AI orchestrationMessages arrive faster than a team can answer them.
Drafts a reply, checks it against policy, escalates to a human.
Every reply logged with its policy and approver.
Federated analytics on Trino and Apache Iceberg — querying 50+ sources where they already live.
Explore the data lakehouseEvery question means another extract, load and rebuild.
Federate every source with no copy and no pipeline.
One query, live data, nothing copied.
A layered system — each pillar builds on the one before it. Start with AI Inventory and build outward from there.
Know every AI system running in your organization.
Trace where data comes from and where it flows.
Ensure the data feeding your models can be trusted.
Protect data at rest, in transit, and in use.
Make sure only the right people reach the right systems.
Keep people accountable for what the AI decides.
Map your controls to the regulations that apply.
Keep a durable record of who did what, and when.
Twelve minutes, scored live against the framework we are audited on. No sales call required to see your number.
On AI governance, lakehouse architecture and what an audit actually asks for.
Yukon Labs has been accepted into Microsoft for Startups, unlocking $100,000 in Azure credits, Azure AI infrastructure and enterprise tooling to accelerate…
Read the postA data catalog indexes what data exists, what it means, where it came from and who owns it. How metadata, column-level lineage…
Read the postAn honest comparison of three data catalogs from the team that deploys them: cost, on-premise viability, lineage quality, analyst experience and time…
Read the postWe build on a small number of platforms and know each one to the depth an audit requires. Hover a logo to see what it covers.
Send a message and someone from engineering — not a call centre — will reply.