An AI assistant on your website and Telegram that answers customers around the clock - from your own FAQs, product data, and systems, not generic internet knowledge - and hands the conversation to your team when a person is needed.
Customers ask the same questions every day - opening hours, prices, stock, order status, how to book. When the answer takes hours, they move on. A traditional rule-based chatbot rarely helps: it only understands the exact phrases someone scripted, and falls apart the moment a question is worded differently.
An AI chatbot understands questions written the way people actually write them. We ground it in your own material - FAQs, product catalogue, price lists, policies - through retrieval-augmented generation (RAG), so it answers from your data instead of inventing one. Where it helps, it also connects to your systems to check live information such as order status or availability.
We build for two channels: a chat widget on your website and a Telegram bot, both running on the same knowledge base. And because a chatbot should never trap a customer, every conversation can be handed over to your team with the full context attached.
An AI chatbot pays off when the same questions arrive every day and slow answers are costing you customers. Consider this service when:
Everything needed to take a chatbot from idea to a channel your customers use every day.
A chat widget styled to match your brand, embedded on any website with a single script, working on desktop and mobile browsers.
An AI assistant on Telegram for your customers, or inside your team’s groups to answer internal questions about products, prices, and SOPs.
Answers grounded in your FAQs, catalogue, price lists, and policies through RAG. Update a document and the chatbot knows - no retraining required.
Need data to stay on your server? Private LLMIntegration with your website, database, or internal APIs so the chatbot can check live information such as order status, stock, or bookings.
When a question needs a person, the conversation is passed to your staff with the full history, and the chatbot says so honestly instead of guessing.
Conversation logs, the topics customers ask about most, unanswered questions to fill gaps, guardrails that keep answers on-topic, and usage cost tracking.
Short phases, each tested on real questions from your customers.
We collect the questions your customers actually ask, decide what the chatbot should handle and what goes to people, and agree on its tone of voice.
Your FAQs, product data, and policies are organised into a knowledge base the chatbot can search, and any system integrations are scoped.
We build the chatbot, the website widget and Telegram bot, the handover flow, and the connections to your systems.
The chatbot is measured against a set of real customer questions before launch, and its answers are tuned until they meet the bar we agreed.
After launch we review unanswered questions and conversation logs, extend the knowledge base, and keep the chatbot improving as your business changes.
Language models, retrieval, and the web and Telegram stack that delivers them.
Not every business needs AI. Here is how the options differ, so you can judge which one fits.
| Manual Customer ServiceYour team answers every message. | Rule-Based ChatbotButtons and keyword menus scripted in advance. | AI ChatbotA language model grounded in your own data. | |
|---|---|---|---|
| Understands free-form questions | Yes | Only the exact phrases scripted | Yes, in natural language |
| Source of answers | Staff knowledge | Fixed scripted replies | Your FAQs, documents, and systems |
| Availability | Working hours only | 24/7 | 24/7, with handover to your team |
| Effort to keep up to date | Training every new staff member | Every new question needs a new rule | Update the documents, not the rules |
| Best suited for | Low volume, complex or sensitive conversations | A handful of simple, predictable questions | Repetitive questions at volume, with people for the rest |
A regular, rule-based chatbot follows a script: it only recognises the keywords or buttons someone programmed. An AI chatbot uses a language model to understand questions written in natural language, then answers from your own knowledge base. It can handle the many ways customers phrase the same question, and it can be updated by editing documents rather than writing new rules.
We build AI chatbots for two channels: a chat widget on your website and a Telegram bot. Both can share the same knowledge base, so an answer updated once applies everywhere.
The chatbot answers from your own documents through retrieval-augmented generation, and we instruct it to say it does not know, then hand over to your team, rather than guess. Before launch we test it against real customer questions, and after launch we review unanswered and low-confidence conversations to close the gaps.
Yes, if your system exposes that data through an API or database we can connect to. We scope these integrations during the knowledge base phase so the chatbot only touches the data it genuinely needs.
Conversation history is stored in your own database and belongs to you. For the language model itself you can use a managed API such as Claude or OpenAI, or - when data must not leave your infrastructure - a self-hosted private LLM, which we also build.
Cost depends on the channels, how large the knowledge base is, which system integrations are needed, and the expected message volume, which also drives the ongoing language model cost. We scope these in a consultation and give you a clear estimate before any build starts.
A chatbot for one channel with an existing FAQ can be ready relatively quickly, while one that connects to several internal systems takes longer. We agree the timeline after mapping your conversations, and we start with the most frequent questions so value shows early.
Practical guides from our engineering team on related topics.
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Picking a first use case that can succeed, checking whether the data is ready, choosing between an AI API and a self-hosted model, running a pilot with a test set, the cost components, and the risks to manage from the first week.
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What the WhatsApp Business Platform offers compared with the WhatsApp Business app, how the 24-hour customer service window and message templates work, going through Meta or a provider, number setup, integrating with your systems, adding a chatbot, and why unofficial tools are risky.
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A guide for business owners considering an AI chatbot: how it differs from a rule-based bot, when it pays off, examples by industry, choosing between website, Telegram, and WhatsApp, what drives the cost, and how to measure the results.
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How retrieval-augmented generation lets a chatbot answer from your own FAQs, catalogue, and policies: preparing documents, chunking, hybrid search, live system data, human handover, and measuring quality.
Tell us which questions your team answers most often - we will show you what an AI chatbot on your website or Telegram could take off their plate.
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