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What PCI DSS, HIPAA, TCPA and disclosure scripts make testable on a voice AI agent call, how to test each control, and what evidence to keep.

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.

How to run regression tests on Pipecat, LiveKit, Retell and Vapi agents after a prompt change, with pass^3 data from one agent tested across six platforms.

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.

Tools to test voice AI agents built on Amazon Connect / Lex: the Lex Test Workbench, the Connect test case APIs, and what neither measures on a real call.

How to test voice AI agents built on the Deepgram Voice Agent API, layer by layer, using the event stream and latency signals that expose each failure.

Voice AI testing for hospitality, retail, ecommerce, real estate and restaurants: the failure mode each vertical forces, and how to assert on it.

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.

What edge case testing for voice AI agents actually covers, plus how to handle regression testing after prompt changes, synthetic user testing, adversarial testing, and multi-agent voice AI testing with Cekura.

How to automate voice agent regression testing with a coding agent, plus running evals in CI and wiring GitHub Actions into the same pipeline.