Train AI on your knowledge
RAG and chunking.
Instead of a generic bot, we split company documents into meaningful chunks and make the chatbot answer only from those chunks, with the source attached.
What you get
Real sources
PDFs, site pages, spreadsheets, catalogs, FAQs, and old tickets.
Chunks that keep meaning
Each piece stands on its own and overlaps the next, so context is not cut in half.
Cited answers
The reply names the document and section, so your team can check it.
How it happens
Collect
We gather the sources and set aside duplicates and outdated files.
Chunk and embed
Each chunk becomes a vector and is stored in a vector database.
Connect a model
GPT, Claude, Gemini, or an open model answers using only the relevant chunks.