IAMD APOLO PLATFORM analyzes every inbound call in less than 100ms, identifying automatic dialers, evaluating ANI reputation and classifying traffic per operator using Machine Learning models trained with your own data.
AMD Detection Accuracy
Reduction of false calls
Human Contact Improvement
Decision Latency
Six integrated modules that work together to provide intelligent detection, traffic analysis, and machine learning.
Real-time detection of answering machines and beep tones. No external libraries required.
Analysis of cause code Q.850, traffic classification, root cause detection, and metrics by carrier.
Auto-training with real audio from your operation. The model updates automatically without manual intervention.
Dynamic reputation score per origin number: High / Medium / Low risk based on behavioral history.
Automatic redistribution of traffic to the best available routes based on real-time metrics.
Unified dashboard: CDR with Q.850 causes, traffic statistics, ANI history and per-operator performance.
IAMD verifies if a number actually exists and detects which company it belongs to, monitoring each call termination reason using Q.850 cause codes. This allows for the accurate identification of invalid numbers, fictitious traffic, and abnormal routing patterns that affect your operations.
Every ANI is continuously evaluated based on call behavior history. The system automatically classifies numbers into three risk tiers and feeds the classification back into routing decisions.
Automatic blocking – number removed from active routing
Active monitoring – flagged for review on next calls
Normal operation – unrestricted routing
The ML engine continuously learns from real audio captured during your operation. Each model is specific to one operator carrier, making detection progressively more accurate over time.
Real call audio from your operation is captured and stored securely for training.
Audio samples are labeled as AMD / Human / Noise with assisted or manual tagging.
The model is retrained incrementally without system downtime or service interruption.
New model version is deployed automatically. Full audit history with metrics per iteration.
Reduce calls to voicemail and increase the effective human contact ratio on outbound campaigns.
Detect channel theft, fictitious traffic and route abuse using real-time Q.850 analytics.
Optimize dialing strategy based on ANI reputation scores and Q.850 termination analysis.
Forensic analysis of routes with complete Q.850 history per operator for compliance and quality review.
| Capability | IAMD APOLO | Traditional | Basic Detection |
|---|---|---|---|
| Real-time AMD detection | ✓ | ~ | ✓ |
| Q.850 cause code analysis | ✓ | ✗ | ✗ |
| Dynamic ANI reputation score | ✓ | ✗ | ✗ |
| Per-operator metrics & evaluation | ✓ | ~ | ✗ |
| ML training with own audio data | ✓ | ✗ | ✗ |
| Intelligent dynamic routing | ✓ | ~ | ✗ |
| Automatic database cleanup | ✓ | ✗ | ✗ |
| Decision latency <100ms | ✓ | ~ | ~ |
Request a demo and see IAMD APOLO in action using your own operation data. Our team will walk you through the platform capabilities and integration options.
Request a Demo