I've spent the last four years shipping AI products across healthcare, sports analytics, social platforms, gaming, and enterprise infrastructure. As COO of GoldRock Holdings, I led end-to-end delivery of platforms that ranged from HIPAA-compliant deployments to real-time computer vision pipelines to consumer applications supporting thousands of daily users.
The gap I kept seeing
Every time I hired a consultant, an agency, or a contractor, the same problems showed up:
They could build, but they couldn't communicate. The engineering was sometimes good, but when it came time to explain the system to a board, a non-technical founder, or a compliance officer — silence. I'd end up translating between my own vendors and my own stakeholders.
They optimized for billable hours, not outcomes. The incentive structure was wrong. A consultant who finishes early makes less money. So things took longer than they should have, and "scope" became a weapon rather than a tool.
They didn't understand operational constraints. Building an AI product for a startup with 6 months of runway is fundamentally different from building one for a Fortune 500 with a 2-year roadmap. Most vendors treated every project the same way.
What I'm building instead
Renado Labs is the consultancy I wish existed when I was on the other side of the table. The model is simple:
- Direct access to the person doing the work. No account managers, no project coordinators, no handoffs to junior devs you've never met.
- Outcome-aligned engagements. Retainer, fixed scope, sprint, or hourly — pick the structure that matches your stage. Every model starts with a scoping call where we define what "done" looks like.
- Operational credibility. I've managed military logistics, deployed to Baghdad, and shipped production AI products. When I tell you something will take three weeks, it's because I've built something like it before — not because I'm guessing.
The background that shapes the approach
Six years as a U.S. Air Force logistics officer taught me that complex systems fail at the interfaces — between teams, between plans and execution, between what leadership thinks is happening and what's actually happening. That lesson applies directly to technical consulting.
An MBA from the University of Illinois (marketing and finance) taught me that the best technology in the world is worthless if you can't explain why it matters to someone writing the check.
And four years of shipping AI products taught me that the gap between "demo" and "production" is where most projects die — and where the most valuable work happens.
What's next
I'm taking on 4 new projects per quarter. If your problem is hard enough and your constraints are real, I want to hear about it.