Who verifies AI? Deep tech startup ArbaLabs looks at the problem of trust

As artificial intelligence (AI) becomes woven into daily life, from chatbots to industrial systems, a quieter concern is emerging. When AI systems make decisions on their own, it is not always clear how those decisions can be verified or who is responsible when something goes wrong. Much of the global AI race has focused on making systems more powerful and capable. Less attention has gone to what happens after deployment, particularly as AI moves beyond cloud servers and into physical environments such as factories, vehicles and infrastructure. In those settings, the ability to trace what an AI system actually did can become critical. One startup exploring this challenge is ArbaLabs, a deep tech company that participated in the 2025 K-Startup Grand Challenge and finished in the final four. ArbaLabs is developing tools designed to verify how AI systems operate on edge devices — machines that run AI locally rather than in centralized data centers. Founder Ashley Reeves describes the company’s work in simple terms. “ArbaLabs builds a way to prove that an AI system is running exactly

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