Voice agent monitoring

Hamming provides real-time monitoring of your production voice agents by ingesting calls via webhooks or direct integration with your voice platform (LiveKit, Pipecat, ElevenLabs, Retell, Vapi, or custom). Every call is automatically scored using the same LLM-as-judge evaluators used in testing, giving you consistent quality metrics across test and production.

Configure proactive alerts for latency spikes, hallucinations, handoff failures, quality threshold breaches, specific guardrail failures, error patterns, and anomalous behavior. Alerts can be sent to Slack, email, PagerDuty, or any webhook endpoint.

Set customizable thresholds per metric and create automated escalation workflows so your engineering and ops teams catch issues before customers do.

Enterprise customers get dedicated Slack channels with direct access to our team for critical production issues.

Yes. Hamming provides end-to-end observability across every stage: speech recognition (ASR), LLM processing, text-to-speech (TTS), and telephony. Trace each interaction from transcription to response delivery to identify exactly where issues occur.

Our root cause analysis automatically traces failures across the ASR → LLM → TTS chain, helping you pinpoint infrastructure vs prompt-level errors in seconds.

Building can be the right call if monitoring or analytics is a core product capability or you have strict data residency constraints. For most teams, buying gets you coverage faster while your engineers stay focused on the agent itself.

If you already have monitoring, Hamming can still add value through voice-native evaluation, OTEL-friendly tracing, and calibrated scoring. See the Build vs Buy guide for a full framework.

Yes. Session replay lets you listen to audio segments where users drop or agents stall, with full transcripts, timestamps, and error codes. Compare pre- and post-fix performance to verify your changes actually worked.

Teams use session replay to understand user frustration moments, identify recurring failure patterns, and drive continuous improvement in agent design.

Hamming flags accuracy drops, intent confusion, and behavioral drift against context-aware baselines, which cuts false positives.

Issues are correlated across ASR, LLM, and telephony layers so you understand whether problems stem from transcription errors, model drift, or infrastructure issues.

Yes. Hamming's analytics dashboard lets you benchmark performance across regions, providers, and user cohorts. Analyze ASR, LLM, and TTS performance to identify which configurations deliver the best reliability.

Yes, if you are monitoring production calls that contain PHI. Hamming signs BAAs for healthcare deployments and supports US-only data residency, configurable PII and PHI redaction, and single-tenant deployment for stricter isolation.

Our RBAC system lets you restrict production monitoring access to authorized personnel while giving contractors testing-only access.

Hamming tracks pass rates, latency metrics (time to first word, total response time), interruption rates, and custom guardrail scores. You can view trends over 30+ days and add annotations to mark deployments or prompt changes.

The performance dashboard shows aggregate metrics alongside per-call details, making it easy to identify systemic issues vs one-off failures.

Yes. With one click, you can convert any production call into a replayable test case. This builds a regression suite from real-world failures, ensuring you never ship a fix that breaks something else.

Teams use this to build "golden datasets" of challenging calls that every agent update must pass before deployment.

Hamming's evaluators compare agent responses against your configured knowledge base, tool outputs, and expected behaviors. We flag responses that contradict provided information, make up facts, or deviate from your agent's defined scope.

Each flagged issue includes the specific transcript excerpt and reasoning, making it easy to understand what went wrong and why.