An experienced colleague retires and takes twelve years of project knowledge with them. Or do they? Ask our RAG knowledge base yourself.
Demo with fictional data. Answers are generated in real time from the emails shown above and grounded with their sources.
Each email is turned into a vector (embedding) and stored in the knowledge base.
For your question, the most relevant messages are found via similarity search.
The language model writes an answer strictly from those messages and names the source.
We build RAG systems on your data: manuals, emails, contracts, tickets. Let's talk.