996: TrueFoundry’s Nikunj Bajaj on How to Get $100M Returns on AI Agent Deployments

About this episode

Nikunj Bajaj discusses how enterprises achieve significant returns from AI agent deployments and the architecture that supports it.

TrueFoundry co-founder and CEO Nikunj Bajaj speaks to Jon Krohn about how enterprises like Nvidia and Siemens are realizing returns of over $100 million from single agent deployments, the AI gateway architecture that makes it possible to connect, observe, and govern agents at scale, and why the familiar advice to “start small” is the wrong way to roll out AI agents inside a large organization. Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/996 Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.⁠⁠⁠ In this episode you will learn: (01:21) What TrueFoundry does and why agents in production need a control plane (06:32) Breaking down the AI gateway: the model, MCP, and agent gateways (16:47) Taming tool sprawl with scoped, read-only MCP access (19:10) Why the agent gateway is the hard part and the kill switch most teams lack (22:24) The five-workflow framework behind $100M agent deployments

People in this episode

Host: Jon Krohn

Guest: Nikunj Bajaj

Topics covered

• AI agents
• enterprise deployment
• AI gateway architecture
• control plane
• agent governance

Keywords

• AI agents
• TrueFoundry
• Nvidia
• Siemens
• agent governance
• control plane
• enterprise AI

Mentioned in this episode

Organizations: Nvidia, Siemens, TrueFoundry

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