AI in Finance: Solving the "Last Mile" Problem

How do you build AI for industries where "average" is a failure? In this episode of Future Proof, Morten Bruun, Member of Technical Staff and Product Manager at Hebbia, breaks down why off-the-shelf models like Claude and ChatGPT aren't enough for the high-stakes worlds of finance and legal. Morten shares his journey from co-founding Flash Docs (acquired by Happier) to developing a platform that manages terabytes of unstructured data for leading investment banks and law firms. We dive deep into: The "Last Mile" Challenge: Why 90% accuracy is effectively 0% for professional standards. Process Engineering: Moving beyond chatbots to create a "canvas" for team-specific workflows. The SaaS-pocalypse: How software companies can differentiate as the cost of code drops to zero. The Technical PM: How AI is compressing feedback loops and turning product managers into builders. Whether you’re a founder navigating the "SaaS-pocalypse" or a product leader integrating AI, Morten’s insights on winning trust in regulated industries are essential. Ready to scale your product’s integrations without the engineering overhead? Visit UseParagon to learn how to ship production-ready integrations in days, not months. Chapters 00:00 - Meet Morten Bruun and Hebbia 00:42 - From Flash Docs to Acquisition: Morten’s Journey 03:15 - Why Finance Needs an Edge (The Problem with "Average" AI) 05:18 - Process Engineering: Moving Beyond the 30,000ft View 08:02 - The Retrieval Gap: Analyzing Terabytes vs. 20 Documents 11:19 - Solving the "Last Mile" for Professional Standards 14:19 - High-Stakes Outcomes: Why Precision Matters 17:16 - The "Canvas" Model and AI Strategists 21:54 - Surviving the SaaS-pocalypse: Differentiation in the AI Age 25:49 - The Changing Role of Product Management and Technical Staff 36:01 - Winning Trust in Highly Regulated Industries 40:43 - Customer Empathy: Focusing on the "Job to be Done"