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AI
RAG assistant

Knowledge Assistant

A grounded internal assistant that answers staff questions from trusted documentation.

Year

2025

Timeline

4 months

Team

4 engineers

Focus

RAG assistant

Results that matter

−60%
faster time-to-answer
92%
staff adoption
100%
answers with citations

The challenge

Staff at a healthcare provider spent hours hunting through scattered policies, procedures and guidelines , and couldn't always trust what they found.

Our approach

We built a retrieval-augmented assistant grounded strictly in approved sources, with a citation on every answer, role-based access control, and an evaluation harness that catches regressions before each release.

The outcome

Time-to-answer fell 60%, 92% of staff adopted it within a quarter, and every response is traceable to its source , so the team genuinely trusts it.

What we delivered

Answers grounded in approved sources
Citation on every response
Role-based access control
Continuous evaluation harness

Tech stack

PythonAnthropicLangChainPostgreSQLRedisNext.js
It's the first internal tool people actually enjoy using. The citations are what won everyone over , they trust the answers.

, Director of Operations, Healthcare provider

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