AI in Financial Compliance: A $75 Million Investment in AML Solutions
AI Agents Target Anti-Money Laundering at Major Global Banks, Cutting Manual Probes
By Michael Novinson | February 12, 2026
A startup founded by a former Meta executive has successfully raised $75 million to utilize artificial intelligence (AI) for financial compliance and the prevention of financial crime. The funding, led by Sapphire Ventures in a Series B round, marks a pivotal moment for Bretton AI, a company transitioning from rudimentary sanctions reviews to advanced anti-money laundering (AML) investigations.
Bretton AI’s co-founder and CEO, Will Lawrence, stated that the capital will enhance the capabilities of the company’s AI agents, enabling them to automate complex data retrieval and analysis for intricate investigations. Lawrence emphasized the potential for Bretton AI to lead in financial compliance solutions, aiming to leverage advanced engineering and product design to harness the latest advancements in AI technology.
Since its inception in 2023, Bretton AI has undergone significant growth, employing 82 individuals and rebranding from Greenlite AI. The company has now raised a total of $95 million, with previous funding including a $15 million Series A in May 2025. Lawrence, bringing valuable experience from his nearly three-year tenure at Meta, is focused on innovating their product offering to meet the growing demands of the financial sector.
As Bretton AI evolves its approach, the integration of AI agents has already streamlined the initial triage process, allowing human investigators to focus on more complex cases that necessitate thorough analysis of fragmented data sources. Lawrence described AI as akin to a paralegal for investigators, proficient in compiling information and summarizing essential findings. He cited historical context, indicating that investigations previously requiring extensive human input are increasingly being expedited through AI capabilities.
Despite advancements, traditional machine learning methods still exhibit limitations, particularly in contextual reasoning and unstructured data analysis. Lawrence pointed out that while such technology can efficiently flag irregularities across large datasets, it often struggles with deeper investigative requirements. In contrast, modern AI agents possess the ability to iterate through workflows, evolving alongside the investigative process.
The strategic transition from fintech startups to large, regulated banks has introduced complex operational demands for Bretton AI. Engaging with these institutions entails interfacing with numerous legacy systems, thus the company has developed robust trust infrastructure for model validation, precision testing, and comprehensive audit capabilities. Lawrence noted that banks typically operate numerous lines of business, necessitating tailored compliance solutions.
In seeking alignment with the institutional culture of major financial entities, Bretton AI rebranded itself from Greenlite AI to better reflect its commitment to stability and growth in compliance processes. Lawrence compared this to the Bretton Woods Agreement, which helped stabilize global markets post-World War II, framing Bretton AI’s mission as a facilitator of institutional growth through enhanced compliance practices.
Competing within a landscape dominated by legacy compliance systems and robotic process automation (RPA) tools, Bretton AI aims to become a leader in financial compliance by integrating the speed of automation with the in-depth reasoning capabilities provided by AI. Lawrence highlighted the importance of market presence, emphasizing how partnerships with significant financial institutions will bolster Bretton’s growth trajectory.
As Bretton AI continues to innovate in the realm of financial crime compliance, the evolution of its AI capabilities may be linked to various MITRE ATT&CK tactics and techniques, including initial access, persistence, and privilege escalation. This alignment underscores the importance of understanding the adversarial tactics that could potentially be employed against financial systems while enhancing the resilience of compliance frameworks in response to emerging threats.