An AI Assistant That Answers From Your Own Documents (RAG)

What it solves

If your support team answers the same questions again and again, new hires search dozens of files for one paragraph, or an account manager spends minutes locating a contract clause, this assistant cuts that search to seconds. The answer is not free text; it is tied to a document.

How it works

1. Your documents (PDF, DOCX, HTML, database records) are chunked and written to a vector index.
2. When a question arrives, the most relevant chunks are retrieved and the model answers only from them.
3. The source file and section are shown beneath the answer.
4. If the index has no sufficient grounding, the assistant says I do not know and hands the conversation to a person.

What is included

• Document upload and re-indexing flow
• A web chat widget or an embedded box on your existing site
• Citations and conversation logs
• Access control: each user only gets answers from documents they are allowed to see
• Optional WhatsApp, Telegram or Slack channel

Where it runs

On your website, in your customer portal, on your WhatsApp Business line, or in Telegram for the internal team. One knowledge base can feed several channels; you do not maintain separate content per channel.

Model and data

The model provider and hosting location are chosen per project. If document content must not be sent to a third-party model, the system can run on open models on your own server. Where the data resides is stated in writing in the agreement.

Timeline and handover

A Starter scope typically goes live within a week. Handover includes the indexing script, content update steps and a usage dashboard, so adding documents does not require a developer.