Obin AI, a US-based enterprise AI company, has emerged from stealth with USD 7 million in seed funding led by Motive Partners.
The round also includes participation from angel investors and advisors Dr Fei-Fei Li and Lukasz Kaiser, figures in foundational AI research and financial services investing.
The company is building agentic AI systems designed to run defined workflows end-to-end within financial institutions' existing controls and audit boundaries. Obin AI has already secured engagements with several large financial institutions globally, with deployments moving from pilot to production in weeks. Additionally, in select deployments, institutions have reported accuracy levels sufficient to rely directly on Obin AI-generated outputs within core workflows.
Architecture and regulatory design
Obin AI's platform is built on an open architecture model in which institutions retain full ownership and control of their models, data, and intellectual property, distinguishing it from closed-ecosystem AI platforms that require proprietary data to be transferred to third-party infrastructure. Every interaction is designed to be auditable, traceable, and aligned to internal governance standards, requirements that are non-negotiable in regulated financial environments where decisions can involve hundreds of millions of dollars.
The platform also addresses the challenge of institutional context preservation, enabling AI agents to reason across multi-decade datasets, legacy documents, and unstructured historical records rather than relying solely on recent or structured data. Target use cases include continuous monitoring, scalable underwriting, and earlier risk detection.
The founding team brings expertise from Google AI and JPMorgan. Co-founder and CEO Apoorv Saxena previously served as Head of AI at JPMorgan and led multiple Google Cloud AI products. Co-founder and CTO Dr Valliappa Lakshmanan is a former Google and Silver Lake executive and author of seven books on artificial intelligence. Obin AI's clients collectively represent over USD 1 trillion in assets under management, according to the company.
Commenting on the news, Apoorv Saxena said the company was built to solve the last mile of AI reliability in financial services, where the final margin of error determines whether AI can be trusted for high-stakes, firmwide decisions.
