Cekura addresses a problem that appears the moment an AI voice agent goes live: conversational agents fail in ways traditional software tests never catch. The platform generates thousands of synthetic conversations against personas, edge cases and adversarial prompts before launch, so teams can gate every deployment on a passing suite rather than discovering bugs in front of real customers.
The product is organized around three loops. Test covers pre-production simulation, instruction-following, tool calls, hallucination and compliance checks. Monitor watches live calls and chats in production, detecting sentiment drift, latency changes, dropped conversations and unresolved intents. Improve closes the loop: Cekura flags a failure, reproduces it in simulation, suggests a prompt or configuration patch, then re-runs the gate to confirm the fix. Alongside this, Cekura Bench publishes head-to-head comparisons of voice platforms and models — turn latency, interruption handling, speech-to-text word error rate — using the same scenarios and scoring.
Cekura targets engineering, QA and CX teams building customer-facing agents in support, sales, healthcare and similar regulated environments. It emphasizes enterprise compliance (HIPAA, SOC 2, GDPR) and integrates with the voice stack teams already use, including LiveKit, Pipecat, ElevenLabs, Cartesia, Retell, Vapi and Speechmatics. A free trial is offered, with pricing available on request.
