VM Hunter

SpeechLLMAI That Understands Audio

99.7% accurate answering machine detection powered by proprietary neural networks trained on millions of real voicemail interactions. SpeechLLM doesn't just measure timing — it understands what's being said.

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Accuracy Rate
99.7%
Classification Time
<50ms
Concurrent Calls
10,000+
Languages Supported
65+

The Problem Traditional AMD Can't Solve

Legacy AMD Limitations

  • Hangs up on real people (5-15% false positive rate)
  • Routes voicemails to agents (15-20% false negative rate)
  • No awareness of call screening systems
  • Cannot understand language content
  • Fails on international accents and non-English audio
  • Breaks on VoIP codec compression

SpeechLLM Advantage

  • 0.2% false positive rate — almost no real humans dropped
  • 0.3% false negative rate — virtually no voicemails to agents
  • Detects CALLGUARD (iOS/Android screening)
  • Analyzes linguistic content and meaning
  • 99.2% accuracy across 65+ languages
  • Handles all codec formats and network conditions

How SpeechLLM Works

  1. 1. Audio Capture

    Raw telephony audio captured from carrier network and normalized across volume levels and codec variations.

  2. 2. Feature Extraction

    Audio converted to mel-spectrograms — 2D visual representations encoding frequency and time information.

  3. 3. Transformer Analysis

    Transformer-based neural network with self-attention mechanisms analyzes the spectrogram across multiple dimensions simultaneously.

  4. 4. Classification Output

    Returns HUMAN, MACHINE, CALLGUARD, or FAILED with an AMDCAUSE such as DISCONNECT, and response time <50ms.

SpeechLLM Classifies All Call Types

HUMAN
Real person answered and is ready to talk
MACHINE
Voicemail, IVR, or automated system
CALLGUARD
iOS, Android, or carrier call screening active
DISCONNECT
Number not in service or disconnected

The Financial Impact

50-Person Call Center

  • 50,000 calls per day
  • Legacy AMD: $250,000 daily revenue
  • With SpeechLLM: $360,000 daily revenue

Annual Value

  • +$110,000 per day
  • +$40,000,000 annually
  • Equivalent to 8-10 new agents

Simple Integration

WebSocket API works seamlessly with VICIdial, Asterisk, FreeSwitch, GoAutoDial, and any dialer supporting audio streaming:

Call Answered
  ↓
Audio streams to VM Hunter via WebSocket
  ↓
SpeechLLM analyzes in <50ms
  ↓
Decision returned: HUMAN / MACHINE / CALLGUARD
  ↓
AMDSTATUS + AMDCAUSE set
  ↓
Your dialplan routes accordingly

No infrastructure replacement needed. No dialplan rewrites. Standard AMD variable compatibility.

Built for Production

Performance
  • Sub-50ms response time
  • 10,000+ concurrent calls
  • Scales horizontally
  • No latency at peak hours
Reliability
  • 99.9%+ uptime SLA
  • Automatic failover
  • Real-time monitoring
  • Dedicated support
Analytics
  • Real-time dashboards
  • HUMAN/MACHINE/CALLGUARD breakdown
  • Detection accuracy metrics
  • Compliance reporting

Experience 99.7% Accuracy Today

Test SpeechLLM on your real calls. No credit card required. Deploy to production in minutes.

Start Your Free Trial

Want to dive deeper into the technology?

Read: SpeechLLM's 8-Layer Architecture for AMD