AI that answers from your documents.
RAG & knowledge bases
In simple words: We connect AI to your own documents so your team or customers can ask questions in chat and get answers with a link to the source.
Retrieval-augmented generation (RAG) systems that let AI answer questions from your own documents, products and data, with sources.
For example: A growing team kept asking the same policy and process questions in chat. Answers arrive in seconds with a link to the source. See how we did it ↓
The problem
Why teams come to us
Generic AI answers are vague or wrong about your business because the model has never seen your documents.
What you get
- Document ingestion: PDFs, web pages, Notion, Drive and databases
- Chunking, embeddings and a vector database
- Answering with citations to the source
- Chat interface or API
- Access control and update schedules
- Evaluation of answer quality
Benefits
What changes for your team
Accurate answers grounded in your data
Sources for every answer
Always up to date
Works in chat, apps or internal tools
How it works
From first call to working result
- 1
Discovery call
A free 30-minute call to map your goal, sources, volume and where the result should land. NDA on request.
- 2
Sample first
We build a small working sample so you can check fields, format and quality before the full build.
- 3
Build & test
We build the full solution, test it on real data and edge cases, and share progress as we go.
- 4
Deliver & support
You get the result, the source code and short handover notes, plus fixes during the support window.
Example project
An assistant that knows the handbook
- The challenge
- A growing team kept asking the same policy and process questions in chat.
- What we built
- We indexed the company handbook and docs into a RAG assistant that answers in chat and links the exact source.
- The outcome
- Answers arrive in seconds with a link to the source.
An illustrative example of a typical RAG & knowledge bases engagement.
Use cases
Where this helps
Tech stack
Tools we use
FAQ
Questions about RAG & knowledge bases
Is my data used to train the AI model?
No. RAG retrieves your documents at question time; with standard API settings your data is not used for training.
Which documents can you use?
PDFs, Word, web pages, Notion, Google Drive, databases and scraped data.
How do you keep it up to date?
We schedule re-indexing so new and changed documents are picked up automatically.
Related services
Often combined with
Ready to talk about RAG & knowledge bases?
Send a short brief or book a call. A senior engineer replies within a few hours.