About MultiplAI

Financial judgment and applied AI, built into one team.

MultiplAI builds AI-assisted due-diligence software for regulated financial institutions, with evidence, traceability, and human accountability designed into the workflow.

The founders

Built across finance and applied AI

Regulated AI requires both an understanding of financial operations and the technical depth to build systems whose outputs can be inspected, challenged, and governed.

Business and financial operations

Henry Chen

CEO & Co-founder

Henry leads MultiplAI's company strategy, client relationships, and commercial development. Before founding MultiplAI, he worked across private equity at Ethos Partners, strategy consulting at L.E.K. Consulting, and financial operations at Kraft Heinz and RBC Capital Markets. He focuses on translating complex institutional processes into practical, scalable operating workflows.

Selected experience

Private equity: Ethos Partners
Strategy consulting: L.E.K. Consulting
Financial operations: RBC Capital Markets and Kraft Heinz

AI and technical systems

Pablo Hernandez-Leal

CTO & Co-founder

Pablo leads MultiplAI's product, technology, and AI strategy, focusing on document understanding, model validation, and explainable systems for regulated institutions. Before MultiplAI, he worked on quantitative machine learning for automated trading and at RBC Borealis on explainable AI. His research background includes peer-reviewed publications and awarded patents.

Selected experience

Multi-agent reinforcement learning: RBC Borealis
Quantitative machine learning: Automated trading systems
Research: Peer-reviewed publications and 3 awarded patents

LinkedIn Google Scholar

Why MultiplAI

Why we built it

Important compliance reviews remain fragmented across documents, spreadsheets, and email. Generic AI can make information faster to produce without necessarily making it easier to verify.

MultiplAI was created around a different premise: AI should help teams find and structure evidence, while people retain authority over every material decision.

How we work

Evidence before confidence

Outputs should be grounded in information a reviewer can inspect and verify.

People remain accountable

AI supports the process; authorized analysts and approvers retain decision authority.

Governance in the workflow

Traceability, review controls, and safe fallback paths belong in day-to-day operations.

Trust & Governance MultiplAI Research Case Studies

Next step

Start with the workflow you run today

Discuss where documents, evidence, review, and approvals create friction for your team.

Discuss Your Workflow