AI · RAG · Enterprise
AI Knowledge Assistant
An enterprise AI assistant that turns internal knowledge into accessible, conversational answers.
Industry
Professional services
Platform
Web · Embedded
Engagement
Extended Product Team
Outcome
Faster access to organizational knowledge.
The challenge
Institutional knowledge lived in thousands of documents across several repositories. New team members spent their first months learning who to ask rather than where to look.
The product
An assistant that answers in the organization's own language and shows its sources. Permissions are enforced at retrieval time, so people only ever see what they are entitled to see.
Approach
Strategy
Selected the question types where a wrong answer is recoverable.
Design
Made citations, confidence, and gaps first-class parts of the interface.
Engineering
Retrieval pipeline with permission-aware indexing and evaluation harness.
Launch
Pilot group, answer-quality review loop, then org-wide rollout.
Capabilities
Grounded answers
Every response links back to the source passage.
Permission-aware retrieval
Access control applied before generation.
Evaluation harness
Answer quality tracked against a maintained question set.
Embedded surface
Available inside the tools people already use.
Architecture
- Retrieval pipeline with chunking and metadata
- Vector database + keyword hybrid search
- LLM orchestration layer
- Permission-aware index
- Python services
- Cloud deployment with usage analytics
Results
—
Answers grounded in cited internal sources
—
Knowledge repositories unified behind one interface
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Quality tracked with a maintained evaluation set
Next project
Healthcare Operations Platform
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