Model ML is helping financial firms rebuild with AI from the ground up

In an interview published on the OpenAI Blog, Chaz Englander, CEO of Model ML, discusses how financial institutions are adopting AI-native infrastructure and autonomous agents to modernize their operations. According to Englander, the shift involves replacing legacy systems with AI-driven workflows that can handle complex tasks like compliance monitoring, risk assessment, and trade execution without human intervention. He emphasizes that these agents operate on a new architecture designed from the ground up for AI, rather than bolting AI onto existing systems. The practical angle for builders lies in understanding how to design autonomous agents that can operate reliably in regulated environments, balancing efficiency with compliance. Englander also highlights the need for robust orchestration layers to coordinate multiple agents and integrate with existing data sources. This perspective underscores a broader trend: AI is not just augmenting existing tools but enabling entirely new workflows that require rethinking infrastructure from scratch.