Conversational AI

Conversational AI is dialog systems (chatbots, voice and text assistants) based on AI/language models that understand natural-language queries and answer in a human-like way: answer questions, help choose, process requests, give 24/7 support, offload operators from routine. Implementation includes choosing a model/approach, connecting to your data and systems, scenarios, limitations and quality control. Honestly about 'AI errs and hallucinates', this is key: language models can output wrong information in a confident tone — make up facts, prices, terms that do not exist ('hallucinations'). For a business this is a risk: the bot can promise a customer something you do not do, or give a wrong answer. So an AI assistant cannot just be 'turned on and trusted' — limitations are needed (answer only within your data), checks, and care in topics where an error is costly (legal, financial, medical). We honestly design protection against fabrications rather than pass AI off as omniscient. Honestly about 'does not fully replace a human': AI is good for frequent, typical, clear queries — and genuinely offloads support with this. But complex, non-standard, disputed or emotional situations (conflict, complaint, a subtle case) must go to a live human. A clear and fast handoff to an operator is mandatory. A bot that 'does not let you' reach a human annoys and harms. We honestly build in a human fallback rather than promise 'AI will replace all support'. Honestly about 'quality depends on data and configuration': the assistant is only as good as the data it relies on and how well-thought-out the scenarios and limitations are. Without a quality knowledge base and configuration even a powerful model will give weak or wrong answers. The value is in the data and configuration, not in the mere fact of 'we have AI'. Honestly about privacy and control: the bot works with user requests (sometimes sensitive) and often via third-party AI services — a matter of data privacy and dependence on the model provider to honestly account for. Honestly about 'does not get smarter by itself': an AI assistant does not improve by itself in your context — it must be maintained, fine-tuned on real dialogs, errors corrected. It is a living process, not 'set and forget'. Honestly about the effect: for suitable tasks it gives fast 24/7 support and routine offloading, but with hallucination protection, a human fallback and quality dependent on data. Honestly about access: a knowledge base/data, readiness to maintain are needed. An important boundary: this is conversational AI; voice assistants (platforms) — 1096; voice scenarios — 1105. The base price starts from 130,000 ₽ (depends on complexity and integrations).

• Support is overloaded with typical recurring questions.
• Answers to users 24/7 are needed without inflating headcount.
• An expectation that an AI bot knows everything and fully replaces support (it does not).
• Hallucination risk, the need for a human fallback and maintenance are not accounted for.

• Conversational AI implementation (model/approach, scenarios, integration with data and systems)
• Protection against hallucinations (answers within your data, limitations, care in sensitive topics)
• A mandatory clear handoff to a live operator (fallback)
• An honest assessment: which queries to give AI and which to people
• Accounting for request privacy and dependence on the model provider
• Honest boundaries (AI errs/hallucinates; does not fully replace a human; quality depends on data; maintenance needed)
• Maintenance and improvement on real dialogs
• Documentation and handover

• A dialog assistant for frequent typical queries offloading support
• Protection against fabrications and a clear operator handoff in complex cases
• An honest assessment: what to give AI and what to leave to people
• Honest boundaries (error risk; not a human replacement; quality depends on data; maintenance needed)

• We assess queries: what is typical (for AI), what is complex (for people)
• We implement the assistant with hallucination protection and an operator fallback
• We maintain it on real dialogs, honestly set boundaries and hand over to you

• Does an AI assistant know everything and answer error-free?

  No, honestly, and this is key: language models can output wrong information in a confident tone — make up facts, prices, terms ('hallucinations'). The bot can promise a customer something you do not do. So we limit its answers to your data, add checks and care in sensitive topics. It cannot just be 'turned on and trusted'. We honestly design protection against fabrications rather than pass AI off as omniscient.

• Will AI fully replace support/operators?

  No, honestly: AI is good for frequent, typical queries and genuinely offloads support. But complex, disputed, emotional cases (conflict, complaint, a subtle question) must go to a live human. A fast and clear handoff to an operator is mandatory — a bot that 'does not let you' reach a human harms. We honestly build in a human fallback rather than promise 'AI will replace all support'.

• Set up AI — and it will get smarter and work perfectly by itself?

  No, honestly: the assistant's quality depends on data and configuration, not the fact of 'we have AI'. Without a quality knowledge base even a powerful model gives weak answers. And it does not improve by itself in your context — it must be maintained, fine-tuned on real dialogs, errors corrected. It is a living process, not 'set and forget'. We honestly build maintenance into the project.