I help small and mid-sized businesses and PE-backed companies make better technology decisions, stop overpaying for software that doesn't fit, and put AI to work on real operational problems.
You've outgrown "the IT person," but a full-time technology executive doesn't make sense yet.
You need a clear read on the technology you bought, and a plan for the first 100 days and beyond.
You're paying more every year for software your team works around rather than with.
Each one is scoped up front, so you know what you're getting and what it costs before we start.
An independent, plain-English view of where your technology stands and what to do next.
Ongoing technology leadership for a set number of days a month, embedded with your team.
Pick one costly bottleneck or overpriced SaaS tool. I'll replace it with software you own.
Talk with the people doing the work and map how it actually flows, using value stream mapping to find where time and money leak out.
Clear recommendations with costs and trade-offs, including when the right answer is to leave something alone.
Lead the change or build it directly. AI speeds up the building; engineering discipline keeps it reliable.
Founder & Principal, Veritas Logic Systems
I'm a technical leader who never stopped building. Over more than 20 years in enterprise technology I've moved from writing code to leading architecture, cloud, and B2B distribution systems work at Michelin, and I still build. Most recently that's meant AI systems and AI-assisted engineering practices, where I've seen firsthand what delivers and what quietly creates new problems.
I started Veritas Logic Systems because the way software gets built has changed faster than most companies can take advantage of it. Large enterprises have teams to sort that out. Growing companies usually don't, and they're the ones paying the most for software that was never built for them.
Veritas means truth. My job is to tell you what's really going on with your technology, recommend what's worth doing, and then help get it done.
AI is helping teams write more code than ever. Much of that gain is being spent checking it. What the research says, and what it takes to get real productivity out of AI coding tools.
Reading AI-generated code takes more skill than writing it, and when an agent gets something wrong, fixing the pull request is only the start.
AI is taking over the work that once trained junior engineers. If companies stop hiring them, they'll eventually run out of senior engineers. Here's a team structure that keeps the pipeline open.
A 30-minute call, no pitch deck. If I'm not the right fit, I'll tell you and point you to someone who is.