About the founder

Scott DeWaters in front of the Fisher College of Business at The Ohio State UniversityScott DeWaters · Founder

Scott DeWaters is an analytics executive at Amazon, an AWS Certified AI Practitioner, and a co-author of AI & supply-chain research with Amazon Logistics leadership. He holds a Specialized Master of Business Analytics from The Ohio State University's Fisher College of Business, and built his career inside some of the largest enterprises in the country — Asurion, Elevance, and now Amazon.

That trajectory has given him a clear view of what enterprise-grade analytics, applied AI, and process discipline can do for organizations with the budget to deploy them. He's built reporting infrastructure, led data strategy, deployed machine learning against real operational problems, and shaped how leadership at scale uses information to make decisions.

The conviction behind CapriSoul, though, comes from outside the corporate org chart. The communities Scott pays the most attention to — the ones where families build wealth, where small businesses outlast recessions, where civic life feels owned rather than rented — share a pattern. The wealth, the decisions, and the feedback all stay close to the people doing the work. A complaint at a local restaurant reaches the owner the same shift; the same complaint at a national chain dies in a department two states away. Local capital gets reinvested down the street. Local taxes fund the parks the owners' kids play in.

CapriSoul is built around that idea: the small businesses, nonprofits, and B-corps anchoring those communities deserve the same operational capability as the conglomerates competing against them. The tools usually aren't gatekept — they just haven't been right-sized for a team of ten. That's the work, and it's why Scott shows up to do it.

The CapriSoul Paradox

How can a brand devoted to the organic also champion AI?

We don't view technology and nature as adversaries. Technology is the precision instrument that unlocks and amplifies the organic. The sampler captures a raw human moment and recontextualizes it. The telescope brings natural wonder into sharp human focus. We deploy AI the same way — a lens that filters the noise and brings the real signal into clarity.

  1. I.

    The Labor Principle

    Our goal is never to displace human labor. It's to democratize survival in an increasingly automated world — ensuring local, diverse founders can compete with conglomerates that benefit from massive infrastructure budgets.

  2. II.

    The Knowledge Principle

    Modern AI is built on the vast corpus of human knowledge. We use it to focus unorganized noise into sound reason — actionable intelligence, not more information overload.

  3. III.

    The Compute Principle

    Not every problem requires the energy footprint of a massive global model. We right-size every solution, weighing compute cost against the friction it eliminates.