Cekura vs valv

Cekura is a comprehensive testing, observability, and self-improvement platform engineered specifically for production voice and chat AI agents. Designed for developers and teams working in the AI and SaaS spaces, Cekura tackles the complexities of maintaining reliable conversational agents by moving beyond simple monitoring and actively closing the optimization loop.

Traditional observability tools often highlight failures and hand the work back to engineering teams. Cekura fundamentally changes this workflow by automatically simulating thousands of real-world scenarios, catching failures, and diagnosing their root causes. It goes a step further by autonomously rewriting prompts and configurations, followed by a full regression sweep to re-validate performance and ensure fixes hold securely without overfitting.

valv is an essential AI infrastructure and data analytics tool designed to make your databases safe for AI agents to query. As development teams increasingly rely on autonomous AI agents and large language models (LLMs) to interact with live data, security and access control have become paramount.

With valv, you can easily connect major databases and data platforms—including Postgres, MySQL, ClickHouse, and PostHog—in a single place. The platform allows you to scope each role down to the specific row level. This ensures that your team's AI agents can work efficiently on live data while never exposing sensitive information or seeing more than you explicitly allow.