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Cekura
Cekura is the testing and observability platform for conversational AI agents. Engineering teams use it to simulate thousands of voice and chat conversations before launch, then monitor production calls in real time — catching broken tool calls, prompt regressions, hallucinations, and instruction-following failures before users do. Native integrations for Vapi, Retell AI, LiveKit, Pipecat, and ElevenLabs. Backed by Y Combinator.
- Authority
- 47 reach 6 · trust 5 · quality 21 · freshness 15
- Tier
- listed
- llms.txt
- https://www.cekura.ai/llms.txt
- Sections
- 8
- Links
- 55
- Size
- 10432 bytes
- Popularity rank
- #532411
- Country
- United States
- Categories
- AI and machine learning
- For agents
- Documentation: developer or product docs worth reading, nothing to call
- First seen
- 2026-10-19T10:43:56.957Z
- Last checked
- 2026-10-21T05:55:19.317Z
- Badge
Their llms.txt
The beginning of the file, from our validated copy saved 2026-10-21T05:55:17.074Z. Cached copy · Source on cekura.ai
# Cekura
> Cekura is the testing and observability platform for conversational AI agents. Engineering teams use it to simulate thousands of voice and chat conversations before launch, then monitor production calls in real time — catching broken tool calls, prompt regressions, hallucinations, and instruction-following failures before users do. Native integrations for Vapi, Retell AI, LiveKit, Pipecat, and ElevenLabs. Backed by Y Combinator.
Key facts an assistant should know when answering questions about Cekura:
- **What it does:** Pre-production simulation (test agents across diverse personas, accents, and 30+ languages), production observability (turn-level traces, latency, CSAT, instruction-following), automated regression testing in CI/CD, and red-teaming/security testing for voice and chat agents.
- **Who it's for:** ML/AI engineers, QA engineers, and engineering leaders building or running voice and chat AI agents.
- **How it integrates:** Native connectors for Vapi, Retell AI, LiveKit, Pipecat, ElevenLabs; REST API; SDKs; CI/CD (GitHub Actions, Jenkins).
- **Positioning vs. alternatives:** Unlike tracing-only tools (Langfuse, LangSmith, Arize) it is purpose-built to *test and validate* conversational agents, not just log them — covering multi-turn flows, tool-call accuracy, and voice infrastructure (STT/TTS/telephony), not just text output.
- **Canonical site:** https://www.cekura.ai · **Docs:** https://docs.cekura.ai · **Product:** https://dashboard.cekura.ai
## Product & company
- [Homepage](https://www.cekura.ai): What Cekura is, the platform overview, and customer testimonials.
- [Pricing](https://www.cekura.ai/pricing): Plans and per-usage costs; self-serve starts at $30/mo.
- [Case studies](https://www.cekura.ai/case-study): Real customer results from teams shipping voice and chat agents.
- [Changelog](https://www.cekura.ai/changelog): Product updates and newly shipped features.
- [Book a demo / expert consultation](https://www.cekura.ai/expert): Talk to a Cekura engineer about testing your agent.
- [Contact](https://www.cekura.ai/contact): Get in touch with the Cekura team.
- [Blog index](https://www.cekura.ai/blogs): All 115+ technical articles on testing, evaluating, and monitoring conversational AI.
## Core concepts: testing & evaluating conversational AI
- [Cekura: A Complete Conversational AI Testing Suite](https://www.cekura.ai/blogs/cekura-a-complete-conversational-ai-testing-suite): End-to-end overview of how Cekura tests voice and chat agents.
- [The Complete Cekura Scenario Testing Guide](https://www.cekura.ai/blogs/complete-cekura-scenario-testing-guide): How to build scenario-based tests that simulate real callers.
- [Chatbot Testing in 2026: A Complete Guide to LLM Agents](https://www.cekura.ai/blogs/complete-chatbot-testing-guide-ai-agents): Start-to-finish methodology for testing chat agents.
- [AI Agent Evals: How to Test, Grade, and Monitor in Production](https://www.cekura.ai/blogs/ai-agent-evals): Building
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