Bringing an AI Knowledge Assistant Into Production Responsibly
A capability story: taking an AI assistant from promising prototype to a governed, dependable production system.
Teams spent significant time locating information scattered across documents, systems, and tribal knowledge. An early AI prototype showed promise but was unreliable, lacked access controls, and could not be trusted for decisions because its answers were neither grounded nor traceable.
We re-architected the assistant as a system rather than a single model call—combining governed data pipelines, retrieval over authoritative sources, permission-aware access, and automated evaluation against representative questions. Guardrails and source citations were built in so every answer could be traced back to its origin, and continuous evaluation monitored quality over time.
The assistant moved into production as a governed capability that respected existing permissions, cited its sources, and was measured continuously for accuracy. The architecture established a reusable foundation for additional AI capabilities to be added safely as needs evolved.
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