# AI for contact centers: voice agents, handoff and call QA

> Mirai Minds builds AI systems for contact centers and other teams that work on the phone: voice agents for inbound lines and outbound campaigns, live handoff to a person, structured data from every call, and automatic quality scoring of recorded calls. We have shipped these for an outbound-calling startup, an admissions counseling team and our own Voice Agents platform.

## Key facts

- **Voice runtime:** Pipecat and LiveKit, or a hosted runtime such as Vapi
- **Handoff:** A person joins the live call; 60 s timeout, then a callback offer
- **Call QA:** Recorded calls scored against a weighted rubric
- **Languages shipped:** English and Hindi; voicemail detection in English and Spanish
- **Telephony:** Plivo, Twilio, SIP


## Use cases

- **Outbound campaigns within calling limits** (shipped by Mirai Minds): A dialer that caps live calls per campaign and overall, keeps to daily dial windows and records a voicemail outcome for each contact.
- **Live handoff to a person** (shipped by Mirai Minds): The agent raises a handoff and the first available person joins the same call. If nobody accepts within 60 seconds, the agent offers a callback.
- **Automatic call quality scoring** (shipped by Mirai Minds): Every recorded call scored against a weighted rubric, with zero scores flagged in red for a manager.
- **Structured data after every call** (shipped by Mirai Minds): A model reads each recording and fills fields such as callback requested, callback time and meeting booked, which drive follow-ups.
- **Live transcription with sentiment** (shipped by Mirai Minds): Calls transcribed as they happen, with sentiment scores alongside the transcript.
- **Suggested answers for human agents** (typical): Answers from the knowledge base shown to a human agent while the customer is still talking.

## What does AI change in a contact center?

Three things, in order of how often they pay off. First, it takes repetitive calls: confirmations, reminders, qualification questions, simple order lookups. Second, it turns every call into data, so follow-ups, callbacks and coaching no longer depend on someone's notes. Third, it reviews calls at a scale no quality team can match by listening.

It does not remove the need for people. Callers still ask for a person, some calls are too sensitive to automate, and a voice agent that cannot hand over is a dead end. Every contact-center system Mirai Minds builds has a way out to a human.

## Which calls should an AI agent take?

Calls with a clear goal and a short list of outcomes. An [outbound campaign](/work/outbound-ai-calling-platform) that confirms details, asks a few questions and books a next step is a good fit. So is an inbound line where most callers want the same few answers. Calls where the caller is upset, the stakes are high, or the answer depends on judgment should reach a person quickly.

We usually start by reading a sample of real call recordings or transcripts and sorting them into those buckets. That sample becomes the first test set.

## How do people stay in the loop?

Through handoff during the call and review after it. On our [Voice Agents platform](/work/voice-agents-platform), an agent that needs a person raises a handoff request, which appears on the team's dashboard. The first person to accept joins the same live call; the claim is atomic, so two people never grab one caller. If nobody accepts within 60 seconds, the agent tells the caller that no one is free and offers a callback, instead of leaving them on hold.

After the call, a model reads the recording and fills structured fields: whether a person answered, whether they engaged, whether they asked for a callback and when, whether a meeting was booked, and the exact words of any conflict. Supervisors work from those fields rather than from memory, and every field links back to a recording a person can check.

## How do you measure quality?

With a rubric, applied to every call. [CallAuditAI](/work/callauditai) scores recorded calls against weighted categories, in one deployment opening and rapport, needs discovery, value and objection handling, and closing, and returns an Excel scorecard with any zero score flagged in red. Managers start with the red flags and listen to those recordings first.

The same scoring works for human and AI calls, which matters: it lets you compare an AI agent with your team on the same rubric before you move more calls to it. Before trusting the totals, we recommend a calibration round in which managers score a sample blind and compare with the model, criterion by criterion.

## What have we shipped for contact centers?

- For an [AI outbound-calling startup](/work/outbound-ai-calling-platform), a Pipecat voice bot over LiveKit SIP, three-layer turn detection, voicemail detection in English and Spanish, a campaign dialer with per-campaign and global live-call caps, and one recording per call.
- For an admissions counseling company, [CallAuditAI](/work/callauditai) for scoring recorded counseling calls.
- For the founder of [Myva.ai and CallPaaS](/work/myva-callpaas-support-and-call-centre), live call transcription with sentiment and GPT-assisted virtual agents.
- Our own [Voice Agents platform](/work/voice-agents-platform), with campaigns, live handoff, post-call data and Hindi calls.

## What does a first project look like?

A short discovery call, then a week of reading your calls and agreeing what success means for each call type. Then a pilot on one call type with one script, one number and a handoff queue staffed by your team, followed by expansion once the scores and the handoff rate look right. The service pages for [voice AI agents](/services/voice-ai-agents) and [custom LLM and document AI](/services/custom-llm-development) go deeper on the technology.

## Frequently asked questions

### Should AI replace our agents?

Rarely all of them. The pattern we have shipped most is AI on the repetitive calls, a live handoff for everything else, and automatic scoring of recorded calls so managers coach from evidence. Where calls are sensitive or complex, keep people on them and use AI to review.

### Can an AI agent call our customers in Hindi?

Yes. Our Voice Agents platform runs Hindi calls on Deepgram Nova-3 speech recognition with Cartesia voices and Indian phone numbers. We test on recordings of your own callers before launch.

### How do you handle consent and recording rules?

They depend on your country and industry, so we agree them with you before launch: what the greeting says, which calls are recorded, where recordings are stored and for how long. For one client we wrote every recording straight to their own cloud storage.

### How long does a contact-center pilot take?

Most builds take two to eight weeks. A pilot on our Voice Agents platform with one script, one number and a handoff queue sits at the short end; custom pipelines, CRM integration and new languages add time.


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Canonical: https://www.miraiminds.co/industries/contact-centres
Last updated: 2026-09-23
Publisher: Mirai Minds LLP, 906 Sarthana Business Hub, Nana Varachha, Surat, Gujarat 395013, India. hello@miraiminds.co