Enterprise Knowledge Assistants
Professional work · Collaborative projectAssistants for finding information across internal documents and technical references.
Information spread across multiple sources can be difficult to find and use consistently.
My contribution
How it worksBuilt web and email ingestion, knowledge indexing and search integrations within a team-designed architecture. Supported deployed assistants and monitored latency, token costs, user feedback and answer quality.
How it works
Enterprise RAG assistants span solutions indexing approximately 500,000 documents. A team-designed architecture combines web and email ingestion, knowledge indexing and search, including retrieval from external technical references.
- Knowledge sourcesWeb, email, documents and technical references
- IngestionProcess incoming content and build knowledge indexes
- RetrievalFind relevant content through search
- Answer generationGenerate responses using retrieved context
- Quality monitoringTrack latency, token costs, feedback and answer quality
Engineering decisions
Source integration
Built web and email ingestion and knowledge indexing within the collaboratively developed solutions.
External knowledge
Integrated search and retrieval from external technical references to support answers alongside internal content.
Operational feedback
Supported deployed assistants serving 200+ requests per day in aggregate, monitoring latency, token costs, user feedback and answer quality.