# Real-Time Voice AI Agent: 70% Calls Without Escalation

> High call volumes, inconsistent quality, expensive 24/7 staffing. Customers waiting on hold.

- Canonical: https://suvegasoft.co.uk/case-studies/voice-ai/
- Client: Enterprise
- Industry: Enterprise
- Timeline: 13 months development
- Technologies: LiveKit, Deepgram, ElevenLabs, OpenAI, React/Next.js
- Published: 2025-01-13T00:00:00.000Z

**Key results:** 70%+ calls without human escalation · Sub-500ms response latency · 40% reduced handle time · 24/7 availability

## Challenge

An enterprise client was struggling with their contact centre operations:

- **Volume**: 50,000+ calls per month overwhelming their team
- **Wait Times**: Customers frustrated by long hold times
- **Staffing Costs**: 24/7 coverage required expensive shift patterns
- **Inconsistency**: Quality varied significantly between agents
- **Scale**: Couldn't hire fast enough to meet demand

They needed a voice AI solution that could handle real conversations—not just simple IVR menus, but actual problem-solving, booking, and sales interactions.

## Solution

We built a full-service voice AI agent capable of handling complex, multi-turn conversations:

### Capabilities

1. **Customer Support**: Answer questions, troubleshoot issues, provide information
2. **Booking & Scheduling**: Check availability, make appointments, send confirmations
3. **Sales Assistance**: Qualify leads, answer product questions, route to closers
4. **Helpdesk**: Technical support with knowledge base integration

### Technical Architecture

The system achieves natural, responsive conversation through:

- **Real-time bidirectional voice** via WebRTC (LiveKit)
- **Natural interruption handling**—customers can cut in naturally
- **Tool calling** for CRM lookups, booking systems, inventory checks
- **RAG integration** for contextual, accurate answers
- **Semantic turn detection** using Silero VAD

### Conversation Quality

Unlike robotic IVR systems, our agent:

- Understands context and nuance
- Handles interruptions gracefully
- Remembers earlier parts of the conversation
- Knows when to escalate to humans
- Sounds natural with high-quality voice synthesis

## Results

The voice AI transformed their contact centre operations:

| Metric                | Before                              | After        |
| --------------------- | ----------------------------------- | ------------ |
| Calls requiring human | 100%                                | 30%          |
| Average response time | 2-5 seconds                         | Under 500ms  |
| Handle time           | 8 mins avg                          | 4.8 mins avg |
| Availability          | Business hours + costly night shift | 24/7         |

### Key Metrics

- **70%+** of calls resolved without human escalation
- **Sub-500ms** response latency for natural conversation flow
- **40%** reduction in average handle time
- **15+** concurrent agent instances running 24/7

### Customer Experience

Callers consistently report:

- Faster resolution than waiting for humans
- Natural conversation flow
- Accurate information
- Seamless handoff when needed

## Technical Details

### Voice Pipeline

```
[Caller] ←→ [LiveKit WebRTC] ←→ [Deepgram STT] → [OpenAI] → [ElevenLabs TTS]
                                      ↓
                              [Tool Calling]
                                      ↓
                          [CRM, Booking, RAG]
```

### Tech Stack

- **Voice Infrastructure**: LiveKit for real-time bidirectional audio
- **Speech-to-Text**: Deepgram for fast, accurate transcription
- **LLM**: OpenAI for reasoning and conversation
- **Text-to-Speech**: ElevenLabs for natural voice synthesis
- **Turn Detection**: Silero VAD for semantic end-of-turn detection
- **Frontend**: React/Next.js dashboard for monitoring and configuration

### Key Design Decisions

1. **WebRTC for Quality**: Browser-standard protocol ensures reliable, low-latency audio
2. **Streaming STT**: Transcription starts before caller finishes speaking
3. **Semantic VAD**: Detects actual end of thought, not just silence
4. **Graceful Escalation**: Seamless handoff to human agents when needed
5. **Full Context**: Human agents see complete conversation history

### Scale

- 15+ concurrent agent instances
- 50,000+ calls/month capacity
- 24/7 availability with automatic failover
- Multi-region deployment for resilience

## Project Details

- **Duration**: 13 months of development and iteration
- **Team**: 2 engineers (1 voice/real-time specialist, 1 full-stack)
- **Status**: Live in production with ongoing enhancement
- **Scale**: 50,000+ calls/month, 15+ concurrent agents

***

_Want to explore voice AI for your contact centre? [Contact us](/contact) to discuss your requirements._