The Case for Data Products
Why enterprise AI investments stall on the data foundation — and why treating data as a governed product is the fix.
Read before
you rebuild.
Four briefings and one book — the case, the standard, and what it takes to make enterprise data consumable by AI agents.
Request a paper. Read it now.
Tell us where to credit it and the PDF downloads the instant you submit — short, plain-spoken, no inbox wait. Prefer to read on the web? Browse the resource guides.
Introduction to FLUID
The open standard explained — the Six Pillars, the SDP/ADP/CDP tiers, the contract, and the compiler.
Data Products by Industry
How the data-product pattern maps onto six sectors — telco, banking, healthcare, retail, energy, public sector.
What Agentic-Ready Means
What it actually takes for enterprise data to be consumable by autonomous AI agents.
The thinking behind the standard.
Before forge-cli, before the Command Center — there was the argument. FLUID lays it out in full: why enterprise data starves AI agents, and the architecture that finally feeds them. The field guide for everyone rebuilding their data foundation for the agentic era.
Research, answered.
What are the field guides?
Four short, plain-spoken briefings on data products and the FLUID standard — the business case, an introduction to FLUID, a by-industry breakdown, and what 'agentic-ready' really means.
How do I get a paper?
Click any paper, tell us where to credit it, and the PDF downloads instantly in your browser — no inbox wait and no follow-up email sequence.
Is there a book?
Yes. 'FLUID: Data Products' is the full argument — why enterprise data starves AI agents and the architecture that finally feeds them. It is available on Amazon.
Who are these written for?
The case for data products is written for leadership; the technical guides for data and platform teams. Most are useful to both — they are deliberately jargon-light.
Map your data products.
Read the case, then see where your enterprise stands. The map tool builds your data-product blueprint in minutes.