Altruist’s February 10th launch of Hazel AI’s tax planning capabilities sent shockwaves through global financial markets, with wealth management stocks plummeting 6-11% across US and UK exchanges. LPL Financial dropped 8.3%, Charles Schwab fell 7%, and Morgan Stanley declined 2.4% as the AI agent’s ability to generate personalized tax strategies “within minutes” triggered what analysts are calling the sector’s first major AI displacement event.

The market reaction underscored a critical infrastructure reality: AI agents are moving beyond demos into production workflows that directly threaten traditional business models. Unlike previous AI hype cycles focused on capabilities, Hazel represents operational deployment where autonomous analysis replaces billable human hours, fundamentally altering the economics of professional services.

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.

WorkFusion raised $45 million in Series funding led by Georgian to scale AI agents that automate financial crime compliance operations, with deployment across 10 of the top 20 global banks processing over 1 million alert investigations daily.

The funding addresses a critical operational bottleneck in the $155 billion financial crime compliance industry, where manual alert review processes overwhelm analyst teams and create regulatory risk for financial institutions facing exponentially growing transaction volumes.