Technology & AI Consulting

Most companies don’t have a technology problem. They have a decision-making problem.

After 30 years, the pattern is always the same. The technology works fine. The decision behind it is where things went wrong; usually the wrong scope, wrong timing, wrong assumptions that nobody challenged.

I’ve spent 30 years helping leadership teams evaluate technology decisions before they get expensive; and diagnosing the ones that already have. I’ll tell you if it’s worth building, what you’re missing, why it’s not working, and whether it’s still delivering.

D.Sc. Information Systems AI · ML · NLP · Data Science
CTO / CIO Fortune 500 to Series A
Eric D. Brown

Anthropic raises $30B in Series G funding at $380B post-money valuation . Anthropic secured $30 billion in Series G funding led by GIC and Coatue, reaching a post-money valuation …

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Half the technology projects I evaluate shouldn't be built — at least not the way they're being pitched.

The vendor demo is designed to sell you. The question is whether it works for your data, your team, and your timeline.

Nobody wants to be the one who says 'we should kill this project.' That's what I'm for.

Co-founded a fintech startup that used NLP and machine learning to analyze market sentiment. Built the core AI models. Got acquired in 2015.

Served as CTO for a financial research platform where I built the AI-powered products, data pipelines, and analytics tools that became the company’s primary revenue drivers.

Created an IT strategic plan for a nonprofit that transitioned them to the cloud and cut their technology spend by 50%.

Built ML-driven revenue forecasting models for manufacturers that saved 20% in raw materials costs. No AI hype; just a good model solving a real problem.

Led development of RAG-based AI systems for an education platform. We built AI agents for tutoring, NLP for analyzing student interactions, measurable improvements in learning outcomes.

Helped Fortune 500 clients optimize their data analytics and reporting, reducing the people-hours needed for data processing by 75%.

1
Startup acquired (NLP + ML for financial markets)
75%
Reduction in data processing time (Fortune 500 clients)
50%
Cut in technology spend (nonprofit cloud migration)
20%
Raw materials savings (ML forecasting models)
$50M
System implementation delivered

Facing a technology decision? Let's talk it through.

No pitch deck. No discovery call script. Just a conversation about what you're trying to figure out.

Colorado Front Range · In-person and remote