Turning messy documents into reliable, automated workflows for mid-market firms in financial services and healthcare.

I'm Jacob, a data engineer turned strategist who has spent his career helping organizations get real value out of their data. Before pursuing my MBA at Northwestern's Kellogg School of Management, I worked as a data engineer and digital innovation leader, guiding cloud migrations, building data pipelines, and developing apps and dashboards that drove measurable operational efficiencies. That hands-on engineering experience, paired with formal business training, is the foundation of how I consult: I'm the same person who scopes the strategy, builds the system, and trains your team on it.

Today I work with mid-market companies in financial services and healthcare: industries where document-heavy workflows quietly consume thousands of hours of skilled professionals' time. Credit analysts rekeying borrower financials, underwriters digging through 200-page submissions, revenue cycle teams drafting appeal letters by hand: these are exactly the workflows modern AI can transform. But most AI pilots never reach production, and the cause is rarely the technology. It's the missing bridge between technical build and organizational adoption. That bridge is what I do.

Outside of client work, I'm a believer that the best way to understand this fast-moving field is to build in it. I prototype document-intelligence workflows with realistic dummy data, write about what's actually working (and what isn't) in regulated industries, and stay close to the evolving governance landscape, from HIPAA to model-risk guidance to the EU AI Act. When I'm not heads-down in a pipeline or a slide deck, you'll find me exploring Chicago's neighborhoods and its food scene.