EPISODE · Apr 14, 2026 · 42 MIN
AI in Finance: Solving the "Last Mile" Problem with Morten Bruun | Product at Hebbia
from Future Proof: Building AI Products that Last · host Paragon
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.Chapters00:00 - Meet Morten Bruun and Hebbia00:42 - From Flash Docs to Acquisition: Morten’s Journey03:15 - Why Finance Needs an Edge (The Problem with "Average" AI)05:18 - Process Engineering: Moving Beyond the 30,000ft View08:02 - The Retrieval Gap: Analyzing Terabytes vs. 20 Documents11:19 - Solving the "Last Mile" for Professional Standards14:19 - High-Stakes Outcomes: Why Precision Matters17:16 - The "Canvas" Model and AI Strategists21:54 - Surviving the SaaS-pocalypse: Differentiation in the AI Age25:49 - The Changing Role of Product Management and Technical Staff36:01 - Winning Trust in Highly Regulated Industries40:43 - Customer Empathy: Focusing on the "Job to be Done"
What this episode covers
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.Chapters00:00 - Meet Morten Bruun and Hebbia00:42 - From Flash Docs to Acquisition: Morten’s Journey03:15 - Why Finance Needs an Edge (The Problem with "Average" AI)05:18 - Process Engineering: Moving Beyond the 30,000ft View08:02 - The Retrieval Gap: Analyzing Terabytes vs. 20 Documents11:19 - Solving the "Last Mile" for Professional Standards14:19 - High-Stakes Outcomes: Why Precision Matters17:16 - The "Canvas" Model and AI Strategists21:54 - Surviving the SaaS-pocalypse: Differentiation in the AI Age25:49 - The Changing Role of Product Management and Technical Staff36:01 - Winning Trust in Highly Regulated Industries40:43 - Customer Empathy: Focusing on the "Job to be Done"
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AI in Finance: Solving the "Last Mile" Problem with Morten Bruun | Product at Hebbia
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