Overview
What it is and the problem it addresses.
A reference design for a knowledge system that ingests documents, answers questions with citations and respects access rules from the source systems.
The problem
Knowledge is spread across drives, wikis and tickets, and generic chatbots cannot be trusted to answer from it or to respect who may see what.
- Document ingestion
- Semantic and hybrid search
- AI answers with citations
- Knowledge-base management
- Access permissions
- Search analytics
Main features
What the concept includes.
Ingestion
Connectors and parsers that keep an index current as documents change.
Hybrid search
Semantic and keyword retrieval with reranking and filters.
Cited answers
Answers linked to passages with the source opened at the right place.
Knowledge management
Collections, owners, freshness flags and review workflows.
Permissions
Source-system access rules enforced during retrieval.
Analytics
Top questions, failed searches and content gaps.
Architecture overview
How the pieces fit together.
- 01
Connectors
Drive, wiki, ticketing and file-share sources.
- 02
Processing
Parsing, chunking, embedding and metadata enrichment.
- 03
Retrieval
Vector and keyword indexes with permission filters and reranking.
- 04
Answer layer
Cited generation with refusal on weak evidence.
Example workflows
How it is used.
Policy question
- 1Employee asks a question
- 2Retrieval applies their permissions
- 3Answer cites the current policy
- 4Feedback improves ranking
Content gap review
- 1Failed searches collected
- 2Owner reviews gaps
- 3New document added
- 4Index updates automatically
Target users
- HR and operations
- Support teams
- Legal and compliance
- Engineering
Potential integrations
- Document stores
- Wikis
- Ticketing
- Identity providers
Security considerations
- Permission-aware retrieval
- Sources never mixed across tenants
- Query and access logs
- Data residency options
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