Posts tagged with "Evaluation"

Learn how to build a self-improving voice agent loop that automatically diagnoses failing evals, applies prompt fixes, catches regressions, and iterates to 100% pass rate.

Developer's guide to voice AI evaluation in 2026. Metrics, scenario testing, hallucination detection, persona QA, and per-stack testing for major voice stacks.

Learn how Cekura's red-teaming framework tests chat and voice AI agents for bias, toxicity, and jailbreak vulnerabilities before they reach production.

Learn how Conditional Actions in Cekura enables dynamic, rule-based testing that adapts to agent responses in real-time, solving LLM hallucination and test flakiness problems.

Learn how Cekura built a custom autoscaling engine using Redis, Celery, and AWS ECS to handle unpredictable spikes, enforce multi-tenant fairness, and scale from one to hundreds of workers.

Cekura lets you replay production calls against new model versions to detect regressions, benchmark performance, and validate upgrades automatically - all from real user data.

Learn why single-turn evaluation methods are insufficient for conversational AI and how multi-turn simulations provide a more accurate assessment of chatbot performance, context awareness, and conversation quality.

Should you switch to GPT-5, Gemini 2.5, or DeepSeek for your Voice AI or Chat AI agents? Learn from real A/B testing, benchmarking, and regression testing insights on choosing the right LLM for Conversational AI.

Braintrust pricing looks simple until overage costs kick in. I broke down every plan, real monthly costs, and where the free tier stops being enough in 2026.

Galileo AI pricing looks simple until you hit production, then issues arise. Here's what the plans actually cost you at real trace volumes in 2026.

Cekura helps teams verify chatbot intent accuracy and entity recognition across real conversations, catching misunderstandings, missing details, and regressions before users do.

Cekura helps teams review and approve NLU diffs for voice bots with precise semantic detection, impact analysis, and automated regression testing so every model or prompt update is safe to ship. HIPAA and SOC 2 compliant.

Evaluate your conversational AI agents for accuracy, safety, consistency, and robustness using Cekura’s full reliability testing suite.

Run voice bot tests with automated pass/fail reports. Automate call simulations, validate responses, and ensure reliable voice AI.

Cekura is the leading chatbot testing platform for AI teams. Automate pre-deployment validation, monitor live chatbot performance, and integrate continuous testing into CI/CD pipelines. Ensure reliable conversations across edge cases with custom metrics and real-time observability.

Cekura is the leading AI chatbot testing platform. Automate scenario generation, regression testing, and production monitoring to build reliable, compliant, and scalable conversational agents.

Automated AI agent evaluation with Cekura. Test, monitor, and improve voice and chat agents using scenario simulation, metrics, observability, and regression testing.

Learn how to test and evaluate voice agents effectively. Discover how Cekura provides automated performance testing tools for voice agents, covering simulation, monitoring, and continuous improvement.

Discover the best AI voice testing platforms in 2025. Learn why Cekura leads with automated scenario generation, voice personas, latency monitoring, regression testing, and production call observability for reliable AI voice agents.