What Conversational AI means in practice
Conversational AI is the umbrella over chatbots, voice agents and virtual assistants — any system whose primary interface is natural-language dialogue. The modern architecture combines an intent classifier (does the user want balance, transfer, complaint?), retrieval (what does our policy say?), generation (a natural-language response), and orchestration (when to hand to a human, when to step up to authentication, when to call a downstream system). The metric that matters in enterprise deployment is deflection rate — the percentage of inbound contacts the bot resolves end-to-end without human intervention — net of any deflection-induced re-contact. MindMap's ChatNext typically deflects 50–70% in regulated industries, on sovereign infrastructure, in multiple languages.
Related terms
Intent classification →
The NLU step of mapping a user's free-text or speech input to one of a curated set of "intents" the system knows how to handle.
AI voice agent →
A conversational AI system designed for voice channels — combining ASR, intent + dialogue logic, and natural-sounding TTS to handle calls end-to-end.
Deflection rate →
The percentage of inbound customer contacts that a conversational AI system resolves end-to-end without human handoff.
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All 62 terms, in plain language
Sovereign AI, RAG, agentic AI, IDP, MLOps and the regulations that shape enterprise AI.