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Jack Morris
Jack Morris

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Building AI Voicebots? Your Legacy VoIP System Might Be the Problem

You've built an amazing AI voicebot with GPT-4 and Whisper. It works perfectly in testing. Then you plug it into your production VoIP system and:
❌ 3-second delays between responses
❌ Calls drop at 50+ concurrent sessions
❌ Audio quality issues during AI processing

The voicebot isn't broken. Your VoIP infrastructure is.

Why Legacy Systems Fail with Voicebots

Modern AI voicebots need:

  • <200ms latency for natural conversations
  • Real-time bidirectional streaming (not traditional IVR)
  • Voicebot connectors to bridge VoIP ↔ AI APIs
  • Scalable architecture for concurrent AI sessions

Your 10-year-old FreeSWITCH setup? Built for basic call routing, not real-time AI.

Chatbot ≠ Voicebot

Chatbot ≠ Voicebot

What "Voicebot-Ready" VoIP Looks Like

Core components:

Caller → SIP Gateway → Voicebot Connector → AI APIs
                              ↓
                    Audio Processing
                    Session Management
                    Fallback Logic
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Modern stack:

  • Kamailio for SIP routing (10K+ calls/sec)
  • FreeSWITCH for media processing
  • Custom connector (Node.js/Python microservice)
  • Cloud AI (Azure Speech, OpenAI, Google)
  • Redis for session state

Results:
✅ 2000+ concurrent voicebot sessions
✅ Sub-300ms end-to-end latency
✅ Horizontal scaling
✅ AI provider failover

Upgrade Signs

Time to modernize if you're seeing:

  • Planning AI voicebot integration
  • Maxed at <500 concurrent calls
  • No API support for integrations
  • End-of-life software versions

Quick Migration Path

  • Phase 1: Add voicebot connector (10% traffic test)
  • Phase 2: Upgrade media layer
  • Phase 3: New SIP routing (parallel run)
  • Phase 4: Full migration
  • Timeline: 3-6 months

If you're building voicebots in 2025, your VoIP infrastructure isn't just infrastructure—it's part of your AI product experience.
Building AI voice solutions? What challenges have you faced? 👇

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