How Capital One Delivers Multi-Agent Systems with Rashmi Shetty - #765

About this episode

Rashmi Shetty discusses Capital One's approach to designing and deploying multi-agent systems in a regulated environment.

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. The complete show notes for this episode can be found at https://twimlai.com/go/765.

People in this episode

Host: Sam Charrington

Guest: Rashmi Shetty

Topics covered

• multi-agent systems
• generative AI
• customer experience
• enterprise AI
• AI governance
• developer experience

Keywords

• multi-agent systems
• generative AI
• Chat Concierge
• intent disambiguation
• AI governance
• developer experience
• model specialization
• closed-loop learning

Mentioned in this episode

Organizations: Capital One

Products: Chat Concierge

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