Enhanced Call Debugging with SIP Status Tracking

Sumanyu Sharma
Sumanyu Sharma
Founder & CEO
, Voice AI QA Pioneer

Has stress-tested 1M+ voice agent calls to find where they break.

December 9, 20243 min read
Enhanced Call Debugging with SIP Status Tracking

Enhanced Call Debugging with SIP Status Tracking

A customer spent three days debugging what they thought was a model issue. The agent kept "failing" on certain calls—no completion, users hanging up frustrated. They rewrote prompts. Tested different LLMs. Nothing helped.

Then we looked at the SIP logs. The calls were being terminated by the carrier before the agent even finished speaking. It wasn't a model problem. It was a telephony problem. Their SIP provider was timing out on responses over 4 seconds.

We added SIP status tracking after seeing this pattern too many times: teams blaming the model when the logs tell a different story.

Quick filter: If you can’t tell whether the agent failed or the carrier dropped the call, you’re debugging blind.

What's New

  • Call termination identification
  • Real-time SIP status tracking
  • Comprehensive session logging
  • Detailed connection state monitoring
FeatureWhat it showsWhy it matters
Call termination identificationWho ended the call and whySpeeds root-cause analysis
SIP status trackingProtocol-level status codes in real timeFlags failures before users complain
Session loggingFull call event timelinesReplays exact failure points
Connection state monitoringState changes across the callDetects instability and drop-offs

Why It Matters

Quick issue identification and resolution are crucial for maintaining efficient voice AI operations. With enhanced debugging capabilities, you can:

  • Accelerate Troubleshooting: Immediately identify who ended calls and why
  • Improve Reliability: Monitor SIP status and connection states in real-time
  • Reduce Downtime: Quickly pinpoint and resolve communication issues
  • Optimize Performance: Track and analyze call session metrics

These tools enable teams to maintain high-quality voice AI services while minimizing debugging time and effort.

We added this after too many incidents where teams blamed the model, but the SIP logs told a different story.

How to Use

To access the new debugging features:

  1. Navigate to your Hamming AI dashboard
  2. Select a voice agent
  3. Open the call logs
  4. View enhanced termination and SIP status details

Key Features

Call Termination Tracking

  • Agent-specific identifiers
  • Timestamp correlation
  • Clear termination indicators
  • Detailed event logging

SIP Status Monitoring

  • Protocol-level insights
  • Connection state visualization
  • Error code identification
  • Real-time status updates

Looking Forward

These debugging enhancements demonstrate our commitment to making voice AI development more efficient and accessible.

Stay tuned for more updates as we continue to improve the voice AI testing experience!

Frequently Asked Questions

SIP status tracking tells you how a call was set up and why it ended (for example, carrier busy signals vs upstream outages). It’s one of the fastest ways to separate “the agent broke” from “the call never connected” and to debug reliability issues without guesswork.

They pinpoint where the failure happened. A spike in connection errors suggests telephony/carrier issues; a spike in mid-call termination codes can indicate network instability or upstream vendor problems; clean connection metrics with poor task completion usually points back to the agent’s conversation logic.

Hamming surfaces SIP status and call termination reasons alongside the rest of the call trace, so you can quickly tell whether a failure was a connection issue, an upstream vendor problem, or an agent behavior regression. This makes it easier to triage failures across large test runs.

Alert on sudden changes in connection success rate and spikes in specific termination codes, especially when they correlate with geography, carrier, or time-of-day. If you can’t tell “carrier issue” vs “agent issue,” you’ll chase the wrong fix. Trend-based alerting catches outages before customers complain.

Sumanyu Sharma

Sumanyu Sharma

Founder & CEO

Previously Head of Data at Citizen, where he helped quadruple the user base. As Senior Staff Data Scientist at Tesla, grew AI-powered sales program to 100s of millions in revenue per year.

Researched AI-powered medical image search at the University of Waterloo, where he graduated with Engineering honors on dean's list.

“At Hamming, we're taking all of our learnings from Tesla and Citizen to build the future of trustworthy, safe and reliable voice AI agents.”