Services
AI & Data Agents
A natural-language data agent is only as trustworthy as the semantic model it is grounded in.
An agent pointed at ungoverned tables will answer confidently and wrongly. Conformed dimensions, documented measures, enforced row-level security and a verified Gold layer are what make an agent safe to put in front of an executive. The architecture work is the prerequisite for the AI layer, not a separate track.
The sequence
01
Govern the model
Conformed dimensions, documented measures and security enforced at the model, so a question has exactly one correct answer regardless of who asks it.
02
Ground the agent
The agent answers from the governed semantic model rather than from raw tables, so its answers inherit the definitions and the access rules already agreed.
03
Surface it where people work
Access sits inside the reporting experience people already open, not in a separate chat tool that has to be adopted on its own.
What we deliver
- A data agent grounded on a governed semantic model, not on ungoverned tables.
- Measure and dimension definitions written down and reviewed before the agent is pointed at them.
- Row-level security enforced at the model, so the agent cannot answer around it.
- Surfacing inside the existing reporting experience rather than as a standalone chat tool.
What has to be true first
- A conformed Gold layer, with entities agreed across domains.
- Documented measures, with the definition and the owner recorded.
- Security enforced at the model, not applied per report.
- Verification tests passing on the layer the agent will read.
Start with the model
We read the estate you have, say plainly what the agent would be grounded on today, and sequence what to fix first.
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