AI Support that knows your product
It answers customers on your website and in messengers around the clock — from your documentation, guides, and past tickets. The hard cases it hands off to a human specialist along with the full context of the conversation.
Why support can't keep up
Most tickets are the same questions, and the answers are already in the documentation.
Customers wait hours for a reply
Overnight and on weekends the tickets pile up. By the time someone replies, some customers have already gone to a competitor or left a bad review.
The same questions over and over
Up to 70% of tickets are routine: how to pay, where the documents are, why something isn't working. Your specialists answer them on a loop.
Knowledge lives in people's heads
A new hire takes months to get up to speed, and some answers are known to just one person — who's on vacation.
What AI Support does
It learns from your knowledge base, guides, and past conversations — and answers the way your best specialist would.
- Answers on your website, in Telegram, and by email — instantly, around the clock
- Draws on your documentation, guides, and history of resolved tickets
- Asks for details when a question is unclear
- Hands the hard cases to a human specialist along with the conversation history
- Guides the customer toward the goal: a request, a payment, a booking
- Shows what people ask about most — a signal for improving the product
How we launch it
Gather the knowledge
Documentation, guides, FAQs, ticket history
Train it on them
The model answers strictly from your materials, without making things up
Put it on a channel
A widget on your site, a Telegram bot, or an email connection
Review and refine
We go through real conversations and expand the knowledge base
The first months — with a dedicated manager
The AI is not launched “as is” and left unattended. For the first 1–3 months a dedicated manager runs your process: tunes the system to you, checks every result and fixes mistakes — while the AI learns on your real data in parallel. Nothing goes live without a human in control.
Dedicated manager
A dedicated specialist runs your process by hand together with the AI: tunes it to your documents and rules, checks every result, corrects mistakes. The system learns on your data.
Autopilot or ongoing support
Once quality is stable, you decide: move the process to autopilot (cheaper, the AI works on its own, the manager on standby) or keep permanent support.
Ongoing oversight, if you want it
For critical processes — primary documents, paid ads, contracts — many keep the manager for good: they backstop it, develop scenarios and own the result.
This removes the main fear of automation — “what if it makes a mistake”. Until the AI has proven its accuracy on your tasks, a human is accountable for the result. We agree the format and cost of support around your process.
Where your data is stored
Conversations with customers contain personal data, so processing runs on our infrastructure in Russia or on your own server. The model answers only from your materials — it doesn't send the content of conversations to foreign services or use it to train anyone else's models.
More about a local neural network on your own server →FAQ
Related reading
We cover this topic in more depth on the blog
Building a Support Chatbot That Doesn’t Hallucinate
A support bot stops inventing answers when it replies from your documentation through RAG and escalates honestly. How that differs from scripted bots and from bare ChatGPT.
AI Chatbot vs Scripted Bot: Which One You Need
A script is predictable for clear-cut processes; AI understands free-form questions but costs more. The comparison, and why a hybrid usually beats either alone.
Adding an AI Assistant to Your Website
An AI assistant answers visitors instantly from your own content, guides them to an enquiry and escalates the hard cases. Embedded on top of the existing site.
We'll launch it on your documentation
Show us your knowledge base or website — we'll build a demo of AI Support on your own materials.
Let us try it on your data
Describe the task and send a couple of typical documents or examples — we will show how the system handles them, before any contract.