By Anshika Mathews · AIM Media House
For years, the autonomous vehicle industry has relied on rigorous simulation techniques to refine self-driving technology. Engineers have spent countless hours testing, evaluating, and iterating on systems to ensure reliability in an unpredictable world.
Now, the same approach is being applied to a different kind of automation: AI voice and chat agents. Brooke Hopkins , a former tech lead at Waymo, saw a familiar challenge when she transitioned from self-driving cars to AI agents.
At Waymo, she helped develop the infrastructure for testing and evaluating autonomous systems, ensuring they could navigate complex environments safely. When she turned her attention to AI agents, she realized the industry was struggling with the same core problem: reliability.
“When I left Waymo, I realized a lot of these problems that we had at Waymo were exactly what the rest of the AI industry was facing,” Hopkins told TechCrunch.
“But everyone was saying that this is a new paradigm, we’re having to come up with testing practices from first principles and that basically we all have to recreate everything.
And I looked at that and said, wait, we’ve spent the last 10 years in self-driving figuring out how to do this.” That realization led to the creation of Coval, a San Francisco-based startup dedicated to evaluating AI agents through automated simulations.
Founded in 2024, Coval builds large-scale testing environments for voice and chat AI, much like how Waymo simulates millions of driving scenarios to improve its autonomous vehicles.
Hopkins formally shaped the idea while participating in Y Combinator’s Summer 2024 batch, and by October, Coval was ready to launch publicly.
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