Service
RAG on company documents
Retrieval-augmented generation (RAG) lets staff ask questions in plain language and get answers grounded in your documents (policies, contracts, manuals, tickets or knowledge bases), with links back to the source.
What you get
- Answers that reference the documents they came from
- Document access respecting the permissions you define
- An evaluation set so answer quality can be measured, not assumed
Typical scope
- Document ingestion pipeline (PDF, Office, HTML, wikis, ticketing exports and similar)
- Chunking, embedding model selection and vector store setup
- Retrieval tuning, re-ranking and citation formatting
- Simple chat interface or API for your own applications
- Evaluation against a question set agreed with your team
Technical detail
- → Hybrid retrieval (keyword + vector) where it improves results
- → Incremental re-indexing so new documents appear without full rebuilds
- → Metadata filters for department-, client- or role-level access
Scope and pricing are agreed per engagement. Implementation is a fixed, one-time fee; infrastructure is paid directly to your provider; ongoing support is optional and priced separately.
Ready to talk through your requirements?
Tell us the use case, where it should run and how many people will use it. We will take it from there.