Internal knowledge assistant
Staff ask in plain language and get a cited answer from policy, SOP and product documentation.
Services / RAG & Knowledge Systems
Grounded answers
RAG & Knowledge Systems
Retrieval systems that answer strictly from your approved documents, with citations and no invention.
Typical stack
Vector searchEmbeddingsHybrid retrievalpgvectorEvals
The approach
Built around
Built around
the outcome.
We turn scattered documents, wikis, tickets and databases into a governed knowledge layer, then put a careful retrieval and answering pipeline on top with evaluation, permissions and source citations.
- Answers traceable to an approved source, every time
- Permission-aware retrieval that respects who may see what
- Measured accuracy before anything reaches customers
Scope, model choice and hosting are decided with you against your data-sensitivity and cost constraints. We will recommend the simplest architecture that meets the quality bar.
Use cases
Where this
Where this
gets applied.
Each of these has a measurable baseline we can benchmark an agent against before you commit to a production build.
Customer-facing doc search
Turns a manual nobody reads into an answer engine on your site.
Contract and document Q&A
Ask across a document set and get the clause, the page and the context.
Sales enablement
Instant, accurate product and pricing answers while the rep is still on the call.
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