Former GitHub CEO Thomas Dohmke has secured a record-breaking $60 million seed round for Entire, the largest seed investment ever for a developer tools startup. The round, led by Felicis Ventures at a $300 million valuation, directly addresses what Dohmke calls the “agent boom” crisis—where massive volumes of AI-generated code overwhelm traditional development workflows.

This infrastructure play comes as enterprises grapple with a fundamental mismatch between legacy development processes and AI agent capabilities. While coding agents like GitHub Copilot have accelerated code generation, the industry lacks essential infrastructure to manage, review, and coordinate the output from multiple AI systems.

Financial institutions spend over $60 billion annually on compliance operations in North America alone, yet 95% of alerts generated by legacy anti-money laundering systems are false positives. Bretton AI’s $75 million Series B, led by Sapphire Ventures, represents a decisive shift toward autonomous agent infrastructure for the financial crime operations bottleneck.

The company, formerly known as Greenlite AI, rebranded to Bretton AI alongside the funding announcement—an homage to the Bretton Woods agreement that established the modern financial system. The parallel is deliberate: CEO Will Lawrence positions AI agents as a similar inflection point for how regulated institutions operate at scale.

Gather AI has secured a $40 million Series B led by Smith Point Capital, the firm of former Salesforce co-CEO Keith Block, bringing its total funding to $74 million. The round validates the Carnegie Mellon-founded startup’s Physical AI platform, which uses classical Bayesian techniques—not LLMs—to power autonomous systems that actively map and monitor warehouse operations.

This investment marks a critical inflection point for AI infrastructure, shifting focus from purely digital, text-generating agents to systems that must operate reliably in the physical world. As enterprises seek to scale automation beyond the data center, a new class of Physical AI infrastructure is emerging to solve the critical bottlenecks of real-world deployment across logistics, manufacturing, and field services.