Coval

Hi Product Hunt Community 🐱👋 I’m Brooke, Founder of Coval! Today, we’re excited to launch Coval, a platform that transforms how you test, debug, and monitor voice and chat agents. Simulate thousands of scenarios from a few test cases. You create the prompts, we simulate environments to test your agents from all directions. 👉 Why did I build Coval? Before founding Coval, I led the evaluation job infrastructure team at Waymo, building simulation tools that tested every code change to ensure the Waymo Driver improved with every iteration. This shift from manual testing on racetracks to scalable, automated simulation transformed autonomous vehicles from early prototypes into reliable systems now navigating the streets of San Francisco. Today, AI agents face similar challenges: promising prototypes often hit reliability roadblocks as they scale. Drawing on my Waymo experience, I built Coval to bring automated simulation and evaluation to AI agents, helping teams move faster and deliver reliable, real-world performance. Coval’s mission? To ensure AI agents can be trusted with critical tasks, just as simulation helped unlock the potential of self-driving cars. It’s a tool built by developers, for developers—designed to save time, increase confidence, and eliminate the headaches of conversational AI development. ❓What Problems Does Coval Solve? 👉 Manual Testing Wastes Time Manually calling or chatting with agents is inefficient. Coval integrates into your CI/CD pipeline, running 1000s of simulations automatically with each prompt change. This saves time, increases test coverage, and boosts confidence in production performance. 👉 Debugging is a Nightmare Fixing one issue often breaks something else. Coval eliminates this frustration by providing actionable insights into agent workflows, tracking metrics for each simulation to help you pinpoint and resolve problems effectively. 👉 Production Monitoring is Hard Identifying the root cause of agent mistakes in production can be a nightmare. Coval’s monitoring offers immediate, actionable insights into custom metrics like LLM-as-a-Judge or tool calls, making it easier to ensure reliable performance. ❓Why Us? Our team brings deep experience in LLM evaluations at Berkeley & Stanford, building distributed systems for Fortune 500 companies, and crafting intuitive user interfaces. 🚀 Special Launch Offer As part of our Product Hunt launch, enjoy a free 2-week trial with personalized onboarding. We’ll help you set up custom metrics, run your first evaluations, and get the most out of Coval. 👉 Start Your Free Trial: https://www.coval.dev 👉 Check out our Docs: https://docs.coval.dev/overview 👉 Book a Demo Call: https://cal.com/bnhopkins/demo Excited to help you ship reliable AI agents faster! P.S. Drop by the comments—we’d love your feedback!

It's exciting to see this launch. Congratulations, Brooke and team! When we all first started building voice agents on top of the new generation of LLMs, the hard problems were things like phrase endpointing, interruption handling, and squeezing latency out of all the steps in the processing pipeline. Now we have really good frameworks -- both open source and proprietary -- that make it possible to build flexible, capable voice agents that perform well "most of the time." But most of the time isn't good enough for lots of use cases. To get to "performs well all the time" we need great tooling for evals (testing), real-time observability, and performance metrics. Coval's tools are a huge step in this direction and we're all going to benefit from their work.

Congrats @brooke_hopkins3 & the team! I can see your platform becoming an integral part of the tech stack for developing and deploying AI agents. I've seen people outsourcing testing to cheaper countries, your solution by far beats the manual way - I'll be happy to spread the word about it. I am also just curious what's the word play behind the Coval name?

Hey! I'm Rhea, the founding engineer at Coval. I'm so proud to be part of this amazing team that @brooke_hopkins3 has put together. Hanging around in the comments to answer any questions :)

If I am using my agents as a front line of interaction with my clients, I need to make sure I have covered every scenario. Coval makes sure that I cover all my edge cases - the ones that are sure to pop up!

Congrats on the launch, Brooke and team! 👏🏻 This is a much-needed step forward for building reliable AI agents that can walk the talk (and debug the chat). The founder-market fit here is spot on—bringing simulation testing from self-driving to conversational AI is a genius move. Can’t wait to see Coval put agents through the wringer and help teams level up!

Congrats on the launch @brooke_hopkins3 @mwseibel. Can the app integrate with any tech stack, or is it focused on specific tech stacks?