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Voice AI Agents

Voice AI agents that handle inbound and outbound calls, understand natural speech, take actions through your business systems and transfer to humans when needed. Built for support, booking, qualification and verification. Deploy with sub-second response latency and full call audit trails.

Plan a Voice AI Agent Explore the Solutions
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What is a voice AI agent?

A voice AI agent is a system that handles phone calls— inbound and outbound—using speech recognition, natural language understanding and speech synthesis to converse with callers in real time. It detects intent, retrieves knowledge, executes business actions through your APIs and transfers to a human when the situation requires judgment. Unlike a traditional IVR, a voice AI agent holds a natural conversation without rigid menus. It is measured on call completion rate, transfer rate, end-to-end latency and cost per completed call.

Call queues are long during peak hours

Customers wait. A voice agent handles routine calls instantly—booking, status checks, FAQs—leaving agents for complex cases.

Outbound follow-up is manual and inconsistent

Sales and support teams call leads and reminders by hand. A voice agent automates follow-up with consistent messaging.

Verification and booking consume agent time

Identity checks, appointment scheduling and order confirmation are repetitive. Voice agents handle them with audit trails.

After-hours support is limited

Customers call outside business hours and get a voicemail. A voice agent provides 24/7 support for routine queries.

How This Solution Can Be Built

Different situations call for different implementations. These are the most common variants.

Inbound support agent

Handles incoming calls for FAQs, status checks and routing. Transfers to human for complex issues with full context.

Outbound follow-up agent

Calls customers for appointment reminders, payment follow-up, feedback collection and lead qualification.

Booking and scheduling agent

Books, reschedules and cancels appointments through your calendar or booking system.

Verification agent

Confirms identity, verifies information and records responses with full audit trail.

How the System Works

From input to output, each step is engineered for a specific purpose.

1

Call connected

Inbound call received or outbound call placed

input
2

Speech recognition

Caller speech transcribed in real time with low latency

ai
3

Intent detection

System identifies what the caller wants and the relevant knowledge domain

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4

Knowledge lookup

Relevant information retrieved from approved sources

data
5

Response synthesis

Answer composed and spoken back with natural-sounding synthesis

output
6

Action execution

If needed, the agent calls a business API (book appointment, check status, update record)

output
7

Human transfer

If the call needs human judgment, the agent transfers with full context: transcript, intent, actions

human
8

Call summary

Transcript, intent, actions and outcome logged for quality monitoring and improvement

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Production and Enterprise Readiness

What makes this solution work in a real operating environment—not just in a demo.

Latency

End-to-end voice latency is engineered to be under one second for natural conversation flow.

Interruption handling

The agent detects when the caller speaks over it and stops, then resumes—barge-in handling.

Call transfer

Transfers to human agents include the full transcript, detected intent and actions taken.

Audit trail

Every call is logged with transcript, intent, actions and outcome for compliance and quality monitoring.

Multilingual

The system can be configured for multiple languages depending on the speech models available.

How Success Is Measured

The right metrics depend on the solution. These are the measures that matter for this system.

Illustrative system view — metrics shown in the dashboard above are labelled examples, not client results.

End-to-end voice latency

Time from caller speech to agent response, measured at P50 and P95

Call completion rate

Percentage of calls that reach a natural conclusion without abandonment

Transfer rate

Percentage of calls transferred to a human, and whether the transfer was appropriate

Interruption recovery

How well the agent handles barge-in and resumes the conversation

Cost per completed call

Total cost divided by completed calls, including speech, inference and telephony

View related case studies

Plan a Voice AI Agent

Tell us the workflow, problem or system you want to improve. We respond with how we would approach it.

Plan a Voice AI Agent

No finished technical specification required.

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Frequently Asked Questions

Can the voice agent handle interruptions when the caller speaks over it?
Yes. The system uses barge-in detection to recognise when the caller starts speaking over the agent. It stops its current response, processes the caller's new input and resumes the conversation. This is essential for natural phone interactions and is engineered into the speech pipeline.
How fast is the response?
End-to-end latency—from caller speech to agent response—is engineered to be under one second at P50. This includes speech recognition, intent detection, knowledge retrieval, response generation and speech synthesis. P95 latency is monitored and optimised through streaming, caching and model routing.
Can it transfer to a human with context?
Yes. When the agent transfers a call, the human agent receives the full transcript, the detected intent, the actions taken and the retrieved knowledge. The caller does not need to repeat information. The transfer is logged for quality monitoring.
Does it work for outbound calls?
Yes. The voice agent can place outbound calls for appointment reminders, payment follow-up, lead qualification and feedback collection. Outbound calls follow the same intent detection, knowledge retrieval and action pipeline as inbound calls, with messaging configured per use case.
Can it handle multiple languages?
The system can be configured for multiple languages depending on the speech recognition and synthesis models available. Language detection routes the call to the right pipeline. Multilingual capability depends on model availability and is scoped per project rather than claimed as a universal feature.
How do you measure call quality?
Call completion rate, transfer rate, latency, interruption recovery and cost per completed call are tracked. Transcripts are reviewed against evaluation sets. Customer satisfaction is collected where appropriate. Drift detection flags when quality changes over time.