How Capital One Delivers Multi-Agent Systems with Rashmi Shetty
EPISODE 765
|
APRIL
16,
2026
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About this Episode
In this episode, Rashmi Shetty, senior director of enterprise generative AI platform at Capital One, joins us to explore how the company is designing, deploying, and scaling multi-agent systems in a highly regulated environment. Rashmi walks us through Chat Concierge, a multi-agent chat experience for auto dealerships that handles intent disambiguation, tool invocation, and human handoffs to deliver safer, more personalized customer journeys. We discuss Capital One’s platform-centric approach to AI agents and how it separates design from runtime governance, embedding policies, guardrails, and cyber controls across agent threat boundaries. Rashmi shares how the team approaches the developer experience for agent builders, observability, and evals for stochastic, multi-agent workflows; and strategies for model specialization, including fine-tuning and distillation. We also cover standards and abstraction, closed-loop learning from production telemetry, and key lessons for enterprises building agentic systems.
About the Guest
Rashmi Shetty
Capital One
Thanks to our sponsor Capital One
Capital One’s tech team isn’t just talking about multi-agentic AI, they already deployed one. It’s called Chat Concierge, and it’s simplifying car shopping. Using self-reflection and layered reasoning with live API checks, it doesn’t just help buyers find a car they love, it helps schedule a test drive, get pre-approved for financing, and estimate trade-in value. Advanced, intuitive, and deployed: that’s how they stack. That’s technology at Capital One.
To learn more about AI at Capital One, visit capitalone.com/tech/ai/.

