AI chatbot on GPT-4 / Claude / YandexGPT / Gemini / Mistral

An AI chatbot is a conversational website assistant based on a large language model (LLM): it understands a question in plain language, finds the answer in your materials (knowledge base/documents via RAG — 893) and answers to the point, can follow a scenario, collect leads and hand over to an operator. We pick the model for the task (GPT-4, Claude, YandexGPT, Gemini, Mistral) — by quality, price, language and data requirements. Honestly about hallucinations, this is key: LLMs sometimes give a plausible but WRONG answer — this is a property of the technology, not a bug of a specific model. So we build guardrails: answer only from your data, do not make things up, honestly say 'I don't know' and hand the question to a human when uncertain or the topic is critical (legal/medical/financial/money). Without this a chatbot can mislead a client. Honestly about replacing support: a chatbot offloads support (handles routine, works 24/7), but does NOT fully replace it — complex, disputed and emotional cases must be handled by a human. We design a clear handover to an operator, not 'a bot instead of people'. Honestly about quality: answers depend on the quality of your materials (garbage in — garbage out) and the setup; perfect accuracy does not exist, so tests and refinement are needed. Honestly about cost: model calls are paid (per token/API); as requests grow costs grow — we help with optimization (904) and model choice for the budget. Honestly about data/privacy: requests go to the model — sensitive data cannot be sent thoughtlessly; if needed we discuss private/local options. Honestly about vendor dependency: cloud models are a dependency on their prices, limits and availability. Honestly about access: materials for the knowledge base and a place to integrate are needed. An important boundary: this is a chatbot; knowledge base/RAG — 893/868, voice bot — 877, guardrails — 905. Picture this: instead of 'support drowning in routine questions' — the bot takes the routine, leaving the complex to people. The base price starts from 60,000 ₽ (depends on the model, data volume and integrations).

• Support is overloaded with routine repetitive questions.
• Clients get no answer outside business hours and leave.
• An ordinary scripted bot does not understand natural phrasing.
• Fear that the bot will start making things up and harm clients.

• Choosing the model (GPT-4/Claude/YandexGPT/Gemini/Mistral) for the task
• Answers from your materials (knowledge base/RAG — 893)
• Guardrails: do not make things up, 'I don't know', handover to a human
• Handover of complex/critical cases to an operator
• Lead collection and scenario flow
• Honest boundaries (hallucinations, token cost, privacy)
• Answer-quality testing and refinement
• Handover and review with you

• The bot understands natural language and answers from your data
• Support offloading and 24/7 answers
• Protection from making things up (guardrails + human handover)
• Transparent token economics (100% accuracy — does not exist)

• We define tasks, materials, critical topics; pick the model
• We set up data-based answers, guardrails, operator handover
• We test on real questions, honestly set boundaries with you

• What if the bot starts making up wrong answers?

  This is a real risk of language models (hallucinations), and we honestly handle it. We build guardrails: the bot answers only from your materials, does not make things up, honestly says 'I don't know' and hands the question to a human when uncertain or in critical topics (legal/medical/finance). Errors cannot be fully eliminated — so operator handover and review are mandatory, and we build them in from the start.

• Will the bot fully replace my support?

  No, honestly: it offloads support (takes routine, works around the clock), but does not fully replace people. Complex, disputed and emotional cases must be handled by a human. We design a clear handover to an operator, not 'fire support'. So clients get fast answers to simple things and a live person for the complex.

• How much does the bot cost to run and why?

  Besides development, the bot's answers are paid: models charge for processing (per token/via API), and costs grow with the number of requests. This must honestly be planned for. We pick a model for your budget and help with cost optimization (904). Quality LLMs have no 'free unlimited', and promising it would be dishonest.