What is an agentic data vault?
How purpose-built AI agents extend data vault automation beyond code generation, covering source analysis, semantic layers, and governed data products…
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Every article we have published on .
The Human Decisions AI Cannot Make
Patrick Van Deven & Hans Hultgren
Data vault automation for smaller teams: Building on the shoulders of giants
What if your team of ten could run a data vault like the best in the industry? The architecture review meeting is one of the most predictable scenes i…
How do you learn to trust the machine? Introducing the Enterprise Context Store.
"We're going to use AI agents to build and maintain our data platform." A lot of data teams are now seriously considering exactly that: automating mod…
Data foundations for AI: why the transformation layer is the weakest link
Every enterprise with an AI programme has heard the same advice: get your data foundations for AI in order. Clean it up. Govern it.
Schema Drift in Data Vault: Why It's Harder Than a Git Diff
Source systems change constantly. Columns get added, tables get split, keys get redefined, feeds get restructured. In a conventional ETL pipeline, you…
Transformation debt: why your data platform isn't AI-ready
Most conversations I have with data and AI executives follow the same arc. They start with ambition: AI initiatives, semantic layers, copilots. Within…
See it on your estate
One session on your own sources says more than any article
Bring a source system and a question. We connect the context store to it and show you what the agents propose.
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