Conversational AI
What is Conversational AI?
Conversational AI is technology that understands natural-language input and carries on a human-like back-and-forth exchange — combining natural language processing (NLP) to parse what a person means, machine learning to improve over time, and dialog management to track context across turns and decide what to say or do next. It spans both text (chat, messaging) and voice (phone calls, voice assistants), and powers use cases like customer support agents, IVR replacement, and appointment booking.
More detail
Three components work together: NLP/NLU turns raw text or transcribed speech into structured intent and entities, a dialog manager holds conversation state and decides the next action, and a language-generation step produces the reply — in a modern stack, an LLM-based AI agent typically handles all three in one model rather than a hand-tuned pipeline of separate classifiers.
Conversational AI is the umbrella category; an AI agent is the specific implementation pattern (tool-calling, multi-step planning) that most production conversational AI systems use today, and turn latency is the metric that determines whether a voice conversational AI feels natural or laggy.
On Orbit, conversational AI ships as voice and chat AI agents that run on Claude models, hold context across a call or thread, call tools to look up orders or availability, and hand off to a human when the conversation needs it — across phone, SMS, WhatsApp, and web chat.
Frequently asked
- What is conversational AI?
- Conversational AI is technology that lets software understand natural language and hold a human-like, multi-turn conversation over text or voice, combining natural language processing, machine learning, and dialog management rather than matching input against a fixed script.
- What's the difference between conversational AI and an AI agent?
- Conversational AI is the broader category — any system that understands and responds to natural language across a conversation. An AI agent is a specific way of building one: an LLM-based system that can also call external tools and plan multiple steps, not just generate a reply.
- Is a rules-based chatbot considered conversational AI?
- No — a rules-based chatbot matches input against fixed keywords or decision-tree menus. Conversational AI specifically uses NLP and machine learning to understand free-form language and manage open-ended dialog, which is what lets it handle phrasing it wasn't explicitly programmed for.
See also
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