Plain-language answers from your own documents
Knowledge assistants
Retrieval systems that let your team or customers ask a question in plain English and get an answer cited from your contracts, policies, and SOPs.
A knowledge assistant lets your team or customers ask a question in plain English and get an answer pulled from your own documents, with citations. Built on retrieval-augmented generation (RAG), it searches your contracts, policies, SOPs, and manuals instead of guessing, so answers stay grounded and current.
It is the fix for knowledge that is locked in drives and wikis nobody has time to dig through. We set up the vector search, ingestion, and guardrails so the assistant cites its sources and updates automatically as your content changes.
What you get
- Answers pulled from your real documents, with citations
- Less time digging through drives and wikis
- Knowledge that stays current as the source content changes
What we build
- Plain-English search over your documents and SOPs
- Vector database setup, ingestion, and cited answers
- Internal knowledge portals and document Q and A
- Automatic re-indexing as content changes
Typically built with
- OpenAI
- Anthropic
- Supabase
- Pinecone
Knowledge assistants questions
What is RAG?
Retrieval-augmented generation. The assistant retrieves relevant passages from your documents and answers from them, with citations, instead of relying on a model guess.
Will it make things up?
We design it to answer only from your sources and cite them, which is the main way to keep answers grounded and reduce hallucination.
How do you handle our data and privacy?
We work inside your accounts with least-privilege access and do not train external models on your private data without explicit agreement.
Think this fits your business?
Book a call and we will tell you straight whether this is the right first move, and what it would take.