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AI voice agent compliance explained: the 2024 FCC ruling, the TCPA and state duties binding outbound calls, and how to test your agent before it dials.

Call center quality assurance software compared: scoring, calibration, compliance, and how QA changes for AI agents. Includes a 12-point buyer checklist.

Export voice bot analytics data three ways: a CSV download from the Calls page, an API pull you schedule, and a webhook that pushes each completed call.

What p99 latency means for voice AI agents, how p50, p90 and TTFT differ, and why tail latency decides if callers talk over your bot. See the benchmark data.

Post dial delay explained: what PDD measures in SIP, the seven second carrier standard, why it stays invisible to voice AI metrics, and how to test for it.

Testing sentiment analysis for voice agent calls: lexical, prosodic and behavioral signals, real-time vs post-call scoring, and why a score alone shouldn't trigger an action.

Silence and overtalk detection explained: what each measures, why the two trade against each other, and how AI voice agents fail differently. With Cekura data.

Three kinds of tool test OpenAI Realtime API voice agents: native session events, text eval frameworks, and external platforms. Cekura scores real calls.

Ultravox ships call history, recordings and free playground calls, and its Testing and Debugging page is still under construction. How to build a repeatable test suite instead, and why an audio native model has to be scored on audio.

How to optimize voice AI agent cost and performance together: the five billing layers, why the cheapest model is not the cheapest agent, and how to write a latency budget on the tail.

How to measure ASR accuracy for multilingual voice agents, WER versus CER, testing code-switching, and how Cekura tests across 30+ languages.

Compare Cekura against Braintrust, Arize Phoenix, and Langfuse for monitoring live AI chat agents, and see which one catches real conversation failures.