trending
•

25d ago

Cekura Bench - Speech-to-speech model benchmarks on live phone calls

Cekura Bench publishes voice AI benchmarks you can verify. Our new speech-to-speech benchmark tests 9 realtime voice models, including GPT Realtime 2.1, Gemini Live, Grok and Phonic, as complete phone agents on live calls: 82 scenarios, three runs each. Models are ranked on reliability, data accuracy, stalled calls, response time and cost, and every call transcript is public. Cekura Bench also covers voice agent benchmarks and STT benchmarks, with TTS benchmarks coming soon.
•

3mo ago

Cekura - The self-improvement loop for voice agents

Cekura is the testing, observability, and self-improvement platform for production voice and chat AI agents. It simulates thousands of scenarios, catches failures, diagnoses the root cause, rewrites prompts and config, then re-validates with a full regression sweep. Unlike tools that hand failures back to your team, Cekura closes the loop by fixing the agent itself and proving the fix holds without overfitting.
•

7mo ago

Cekura - Observe and analyze your voice and chat AI agents

Out-of-the-box 30+ predefined metrics for analysis on CX, accuracy, conversation and voice quality. Compile perfect LLM judges by annotating just ~20 conversations and auto-improve in Cekura labs. Real-time, segmented dashboards to identify trends in Conversational AI. Smart statistical alerts so that you get notified only when metrics shift from historical baselines. Automated system pings to catch silent production failures.
•

1yr ago

Cekura - Launch reliable voice & chat AI agents 10x faster

Cekura is an end-to-end QA for Voice & Chat AI Agents. Cekura helps Conversational AI companies with pre-production testing and simulation as well as monitoring of production calls to ensure quality and reliability at every stage of development
•

2yr ago

Vocera - Launch voice agents faster with simulation & monitoring

Vocera helps AI developers build production-ready voice agents 10X faster. It generates adversarial scenarios, simulates realistic calls and gives actionable insights to your agents. It also monitors production calls to ensure complete reliability.
•

7mo ago

LLM-as-a-judge based monitoring is not enough for Voice AI

Most teams scaling Voice AI think they can monitor quality with a simple LLM prompt. They are wrong.

An LLM can t hear a "crunchy" voice line, it can t accurately measure a 500ms "barge-in," and it struggles with the nuances of true conversational flow.

When we built Cekura Monitoring, we realized we had to go beyond the LLM. We combined Heuristic and Statistical models with our Metric Optimizer to solve the "Scaling Wall."