AI Assistants and RAG Development
PythonLLMRAGLangChainSo routine questions don’t eat the line — and answers come from your docs
An assistant on your corpus: playbooks, contracts, FAQ. It answers with “where this came from” — not from thin air.
- 1Your documents
- 2Answer with a source
- 3Hard cases to a human
What this is
A knowledge-base assistant answers from your playbooks, contracts, and FAQ and points to the source. It does not invent: if it is unsure, it hands a person what it already found.
Where this is used
Customer support
“How do I return this”, “which papers” — an answer from your memo. An operator steps in only on the hard ones.
New staff
They don’t tap seniors for trivia: they ask the corpus. One playbook, not “what Vasya said by the kettle”.
Sales and tenders
A manager finds a clause in a contract or quote without digging through a 200-file folder.
How it is now
The same questions every day. New hires can’t find the playbook. A generic chatbot invents answers and puts you in front of the client.
What changes
People ask in site chat or Telegram — the reply comes from your files, with a source. If it’s unsure, it doesn’t invent: it hands a person what it already found.
With what you already have
The assistant sits where people already ask: the site and Telegram. A hard topic can become a task for a staff member. Recording leads into CRM is a later step — not a substitute for the corpus.
What to prepare for an estimate
Share sample documents and questions, access restrictions, hosting requirements and escalation rules.
What affects cost and timing
Document quality, formats, updates, permissions and answer evaluation determine the scope. Model and infrastructure costs are separate; RAG does not eliminate model errors.
How we go
- 01
Which documents
What may be shown, what stays internal
- 02
Where they ask
Site, Telegram, internal chat
- 03
When a human
From which point we stop answering and call a person
What you get
- Answers from your corpus with a source
- Hard questions handed to a person
- A log: what was asked and which document fired
Technology
- Language modelWording of the answer
- Corpus searchYour documents only, not the model’s internet
- Site chat / TelegramThe channel where questions already arrive
- HandoffA hard case doesn’t stall in chat
Common questions
- How is this different from plain ChatGPT?
- It answers only from your files and shows where the line came from. A generic chat uses “general knowledge” and can invent a policy you do not have.
- Site chat or Telegram?
- Wherever people already ask: site chat, Telegram, an internal channel. You can change the channel; the corpus stays one.
- What should stay out of the corpus?
- Internal-only material and anything a client must not see. We decide which folders are in before go-live.
