Glossary

AI Voice Agent

An AI voice agent is an AI agent that interacts with users through voice — answering inbound calls, placing outbound calls, and conversing in real time.

AI voice agents combine speech recognition (ASR), large language model reasoning, and text-to-speech (TTS) to produce natural telephone conversations. They integrate with telephony platforms like Twilio, Vapi, or RingCentral to answer real phone numbers, and with CRMs and helpdesks to act on the conversations they have.

Common AI voice agent use cases include 24/7 customer support answering, outbound sales qualification, appointment scheduling, insurance claim intake, and after-hours call coverage. They typically identify themselves as AI (a growing regulatory expectation) and route to human agents on escalation signals.

Enterprise-grade AI voice agents are governed by a policy layer, logged in audit-grade detail, and integrated so they update the same systems human agents use — no parallel stack.

See also
  • AI Agent— An AI agent is a software system that uses a large language model to perceive its environment, reason about tasks, and take actions in external systems on behalf of a user.
  • AI Chatbot (AI Chat Agent)— An AI chatbot — more accurately, an AI chat agent — is an AI agent that interacts with users through text: web chat, WhatsApp, SMS, Slack, Teams, or social messaging.
  • Agent Constitution— An agent constitution is the written policy that defines what an AI agent is authorized to do, what it must refuse, how it escalates, and how it speaks — enforced at runtime by a policy layer.
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More terms in the glossary

AI Agent

An AI agent is a software system that uses a large language model to perceive its environment, reason about tasks, and take actions in external systems on behalf of a user.

AI Chatbot (AI Chat Agent)

An AI chatbot — more accurately, an AI chat agent — is an AI agent that interacts with users through text: web chat, WhatsApp, SMS, Slack, Teams, or social messaging.

Retrieval-Augmented Generation (RAG)

Retrieval-augmented generation (RAG) is an architecture that grounds a language model's responses in a specific knowledge base by retrieving relevant passages at inference time and conditioning the response on them.

Multi-Agent Orchestration

Multi-agent orchestration is the practice of coordinating multiple specialized AI agents to accomplish a task that is too complex or too broad for a single agent.

Constitutional AI

Constitutional AI is an approach to training and deploying AI systems in which model behavior is guided by an explicit written set of principles — a "constitution" — rather than only by reinforcement from human feedback.

Model Context Protocol (MCP)

Model Context Protocol (MCP) is an open standard for connecting AI agents to the tools, data sources, and prompts they need, through a consistent client-server protocol.

See the full glossary

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Enterprise AI Agents

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