Optimizing a voice agent requires more than checking if it can complete a conversation. You need to understand how different dialog strategies behave under real caller conditions and know exactly which version performs better on accuracy, responsiveness, stability, and user experience.
Cekura gives teams a complete A/B testing environment built for voice agents that operate in real multi-turn conversations.
Cekura runs controlled experiments across live-like calls, compares variants on rich conversational metrics, and surfaces precise turn-level issues. Teams use it to test updated prompts, new models, infrastructure changes, or alternate dialog flows before deploying them to real customers.
Real-time voice routing for controlled experiments
Cekura assigns callers to variants instantly with minimal latency and keeps every caller pinned to the same experiment arm for the full conversation. This ensures clean comparisons for multi-turn strategies. You can route experiments by caller intent, user segment, previous behavior, or any metadata you supply. Cekura supports both inbound and outbound test calls across telephony, WebRTC, and websocket integrations, enabling consistent experiment execution at scale.
Speech and NLU variation tracking
Voice experiments often fail because it is unclear whether differences came from the dialog design or from drift in ASR or NLU interpretation. Cekura captures transcripts, speech patterns, and per-turn evaluations using predefined and custom metrics such as instruction following, relevancy, hallucination, interruption patterns, and voice quality. Teams can isolate variant effects and avoid misinterpreting recognition noise as dialog performance.
Latency and turn-taking performance
Cekura measures latency across every turn with mean, P50, P90 and tracks silence issues, infrastructure pauses, and network-driven failures. This makes it possible to compare strategies without adding overhead to TTS or recognition. When variants differ in flow or verbosity, Cekura quantifies their impact on responsiveness.
Outcome metrics that matter
Every variant is scored on the metrics that define success for your use case. Cekura supports task completion, containment, expected outcomes, tool-call success, CSAT, sentiment, interruption handling, repetition, and custom KPIs. The platform attaches turn-level timestamps to each deviation so teams can trace failures directly to a line in the conversation.
Statistical rigor for production-quality decisions
Teams can rerun experiments automatically, compare baselines, and evaluate variance across multiple repetitions. Cekura supports batch-level comparison of model versions, prompts, or infrastructure providers using identical scenarios. This allows accurate assessments even for long or rare-intent conversations.
Complete data capture and instrumentation
Cekura logs user utterances, TTS prompts, NLU outputs, tool calls, conversation state, audio artifacts, and all metric evaluations in a single unified view. Stereo recordings enable precise interruption detection and speech-level analysis ().
Flexible experiment design for real dialog changes
You can test new prompts, reworded instructions, updated flows, fallback policies, repair strategies, or entirely different dialog frameworks. Cekura supports template-based switching and context-aware experiments, including tests that only run when ASR confidence falls below a threshold or when the variant reaches a specific node.
Works with your voice stack
Cekura integrates with Retell, VAPI, ElevenLabs, Pipecat WebRTC, Bland, LiveKit, and telephony providers. Teams can A/B test changes to models, TTS, ASR, or backend infrastructure using the same scenarios and compare results side-by-side ().
Monitoring and anomaly detection
After experiments finish, Cekura monitors real production calls for drift, latency spikes, unexpected tool behavior, or new error patterns. Slack and email alerts notify teams when metrics fall outside normal ranges.
Built-in privacy and compliance
Cekura supports audio and transcript redaction for sensitive data, providing safe experimentation across healthcare and finance environments.
Scales with your volume and workflow
Teams can run many experiments in parallel, segment by agent version, and automate nightly or CI-driven test suites. Load testing tools allow controlled stress tests with increasing concurrency to detect bottlenecks.
Works across omnichannel dialogs
If your workflow spans voice and chat or uses SMS during calls, Cekura maintains context across channels and applies consistent evaluation.