services / rag-applications
RAG & Knowledge Systems
Build search and question-answering tools that retrieve from your own documents and show where answers come from.
Scoped quoteTimeline: Defined after discovery
Where this helps
- Search internal policies and procedures
- Help staff find product or technical documentation
- Answer questions over an approved knowledge base
Scope & approach
Retrieval-augmented generation (RAG) connects an AI application to a maintained knowledge source. We prepare and index approved documents, retrieve relevant passages and provide source references alongside answers. Access rules, document freshness and an evaluation set are part of the implementation. The system should flag missing evidence and make it easy to ask a person.
What’s included
- Document ingestion and indexing
- Semantic and keyword retrieval
- Source references in answers
- Access-aware retrieval
- Content refresh workflow
- Retrieval and answer evaluation
What you take away
- A searchable, maintainable knowledge source
- Answers linked to supporting documents
- A quality baseline and content update process