Safe AI Access to Company Data
Handing AI open access to company data is asking for trouble. I built a governed layer so it answers real questions safely, without ever seeing what it should not.
The situation
A produce enterprise wanted what everyone wants right now: the ability to ask questions of its own data in plain English and get real answers. The risk was equally plain. Handing an AI assistant open access to company systems exposes everything: payroll, grower contracts, customer pricing. And an AI pointed at messy, inconsistent data doesn’t give you insight, just confident-sounding answers built on the same numbers nobody trusted in the first place.
Leadership was past the pilot-program-and-slide-deck stage. They needed someone to design the thing safely and then actually build it.
What I did
I designed the architecture on a principle borrowed from security work: defense in depth, meaning several independent layers of protection rather than one gate.
The foundation was a governed, read-only data layer, curated specifically for AI access. The assistant can’t see the operating systems at all. It sees only a controlled copy of the data, refreshed automatically, with every record carrying one permanent ID. On top of that I added identity and access controls, so the assistant operates under real, named permissions rather than a master key. I classified the data by sensitivity and excluded the most sensitive categories from AI access entirely. The assistant connects through governed interfaces that log every query, so there’s a complete record of what was asked and what was read.
Then I shipped it: a working rollout with real users asking real operational questions, not a demo.
What changed
Questions that used to mean a report request and a two-day wait are now answered in seconds, by the person who asked them. The assistant reads from data leadership already trusts, so the answers hold up. Nothing sensitive is exposed, and every access is logged and auditable. The company got the AI capability its vendors kept promising, built on its own data, without betting the business to get it.