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AI voice agents for contact centers

AI voice agents now answer and make phone calls for businesses. Learn how they work, where they struggle, and what to test before one talks to your customers.

Published

A customer on a phone call at his kitchen table

The short answer

An AI voice agent is software that holds a spoken phone conversation: it listens, works out what the caller needs, takes action in business systems, and replies with a synthetic voice. On a phone line, its quality depends on things you can test: how well it hears, how quickly and naturally it responds, and what happens when it needs a person.

What an AI voice agent is

An AI voice agent, sometimes called an AI phone agent, is an AI agent that works by voice. It answers or places phone calls, understands what the caller says, takes actions such as looking up an account or booking an appointment, and speaks its replies.

It differs from a traditional menu-based IVR because callers speak naturally instead of pressing keys or saying set phrases. It differs from a chat agent because everything happens in real time, by ear, on audio that is often far from clean.

AI agents for customer service

How an AI voice agent handles a call

Many voice agents use a chain of systems. Speech recognition turns the caller's words into text, a language model decides what to do and say, and text-to-speech speaks the reply. Some newer systems process speech directly instead of passing through text.

Before any of this, the audio has to reach the system clearly. Phone audio is often narrowband or degraded by codecs and network conditions, callers use speakerphones in cars and busy rooms, and other voices in the background can be mistaken for the caller.

Hearing

Speech recognition has to handle accents, noise, poor connections, and people talking over each other.

Understanding and acting

The language model interprets the request and uses connected business systems, within the permissions it is given.

Speaking

Text-to-speech has to sound natural and stay clear on a phone line.

Turn-taking

The agent has to know when the caller has finished, reply without long pauses, and stop when the caller interrupts.

How the speech layer fits into a voice AI system

Where voice agents struggle on real calls

Demos usually run on a clear voice in a quiet room. Real calls do not.

Sanas research on noise cancellation for agentic AI describes background noise as one of the biggest barriers to accurate voice AI. It also notes that conventional noise cancellation can make speech sound cleaner to people while removing details that speech recognition relies on.

  • Noise and background voices: a busy room or a speakerphone can cause mishearing.
  • Accents and pronunciation: recognition that works well on some speakers can mishear others.
  • Interruptions and false triggers: background sounds can make the agent think the caller is speaking, so it stops or replies at the wrong moment.
  • Moments that need judgment: a disputed charge or a policy exception can be more than the AI should decide alone.
Inside Sanas ASR-optimized noise cancellation

Where AI voice agents fit in a contact center

Voice agents suit defined, high-volume requests with clear outcomes: checking a status, booking or changing an appointment, answering common questions, or collecting details before a person takes over.

They need more care where conversations carry financial, medical, or compliance consequences. There, the question is not only whether the agent can handle the call, but how a person can step in when it should not decide alone.

Human in the loop AI for customer conversations

How to choose an AI voice agent platform

Compare platforms on the calls you actually take, not on a scripted demo.

  • Hearing: accuracy on your callers' real audio, including accents, noise, and mobile connections.
  • Speed: response time that feels natural, measured on your phone network.
  • Turn-taking: how it handles interruptions, pauses, and background voices.
  • Voice: a natural, clear voice that is disclosed to callers as AI.
  • Actions: which business systems it connects to, and which actions need approval.
  • Human involvement: how a person is alerted, what context they see, and whether they can take over and hand back without the customer starting over.
  • Records: whether every AI action and every human action is recorded.
  • Telephony: how it connects to your phone network and contact center platform.
  • Deployment: where audio and data are processed, which models are used, and whether it can run inside your environment.

Where Sanas fits

Sanas works on two parts of this problem. The first is the speech layer under a voice agent. The Sanas Developer Platform offers a server-side SDK for Speech Enhancement, Accent Translation, and Language Translation, and Sanas ASR-optimized noise cancellation is designed to remove disruptive noise while keeping the cues speech recognition relies on.

The second is keeping a person in command. With Sanas Supervised AI, AI agents take the calls while one supervisor follows up to four conversations and can listen in, guide the AI privately, take over, and hand back. It runs inside your environment, in a private cloud or on premises, on your choice of models.

Explore Sanas Supervised AI

Further reading

Sanas Learn

Common questions

Give your voice agents a person in command.

See how Sanas Supervised AI runs AI calls with one supervisor governing several conversations at once.

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