Unmukt Raizada is the Founder and CEO of TrustEvals, an AI company that helps organizations build and deploy reliable AI with built-in governance, audit, and evaluation. He has 16 years of experience working at the intersection of data and AI. Before TrustEvals, Unmukt held senior data and AI roles at Goldman Sachs and JPMorgan Chase and co-founded the AI software company Thena. He now helps organizations move AI into production with stronger evaluation, traceability, and governance.

As AI systems become more powerful and autonomous, businesses face a growing challenge of ensuring agents behave reliably once deployed in real-world environments. Traditional software testing and basic monitoring may not catch unexpected AI behavior before it creates problems, particularly in sensitive or regulated workflows. How can organizations capture AI's benefits while maintaining the evaluations, guardrails, and human oversight needed for reliable performance?

Unmukt Raizada, an AI systems and evaluation expert, recommends continuously evaluating AI agents instead of assuming successful testing at launch guarantees future performance. He emphasizes combining probabilistic AI with deterministic engineering where mistakes cannot be tolerated, establishing guardrails around agent behavior, and maintaining human intervention at critical points. Unmukt also encourages subject matter experts to apply their workflow knowledge and intuition when designing AI systems, while avoiding unnecessary complexity from excessive numbers of specialized agents.

In this episode of The Customer Wins, Richard Walker interviews Unmukt Raizada, Founder and CEO of TrustEvals, about building reliable AI systems. Unmukt discusses AI harnesses, continuous evaluations, and the role of human expertise in keeping AI agents effective and controlled.