Privian is an AI consulting practice. We design and build production AI systems: RAG pipelines, agentic architectures, and the cloud underneath. Thirty years in enterprise tech, now focused on AI.
Services
Practice areas are the work. Engagement models are how we do it together: fractional leadership, hands-on build, scoped projects, or a fixed-scope readiness assessment.
01 // AI Infrastructure
Full design and implementation of production AI systems: cloud-native, on-prem, or hybrid. Data layer through eval harness.
02 // Cloud & IaC
Infrastructure that works in production, not just in diagrams. Private cloud, hybrid, and multi-cloud patterns drawn from fifteen years before it was called DevOps.
03 // Advisory
Technical leadership for organizations that need an experienced voice in the room: a five-person startup with no tech lead, or a mid-market company navigating a major platform decision.
About
The pattern across three decades has been consistent: show up where the next era is taking shape, then make the transition real for the people who aren't already at the front of the line.
Privian has built cloud infrastructure for nearly every Fortune 100. Privian has also put broadband into rural school districts the big carriers wouldn't touch. The scale is different. The problem (figuring out what the technology actually is and making it work for your specific situation) is the same.
That's what we do now. Take what we learned building at enterprise scale and apply it to any organization ready to put it to work: five people or fifty thousand, mom-and-pop or multinational.
Early 2000s
Co-founded an ISP putting broadband into school districts the carriers wouldn't touch. Ran Pierce College's full data center transformation: virtualized 80% of workloads before "cloud" was a word.
2010
Early SE at DynamicOps. Built what became vRealize Automation. After the VMware acquisition: National Cloud Specialist, early CodeStream CI/CD design.
Mid 2010s
Founding SE at SovLabs. Office of the CTO at CloudBolt. IaC, Kubernetes, and cloud-native at scale across nearly every Fortune 100.
Recent
First SE at Firefly.ai. Founded Privian to build the AI infrastructure the hyperscalers don't sell to.
Now
Consulting on AI infrastructure, agentic systems, and cloud architecture. Writing practitioner-level posts at Echoes of the Machine.
Who I Work With
The patterns that work for a Fortune 100 cloud architecture apply to a local bakery tired of paying the SaaS subscription tax. Scale changes. The thinking doesn't.
Existing infrastructure that needs AI capability added, aging cloud architecture that needs modernization, or a senior technical voice for a specific initiative. National reach, remote engagement.
Founding teams that need a fractional CTO or senior architect to help build the right thing, pick the right stack, and talk credibly to technical investors. We know what that room looks like.
Five employees or fifty. If you're tired of the SaaS subscription tax and want technology that actually works for your business, we can build it. On-site in Central Florida, remote everywhere else.
Mission-driven organizations deserve the same technology access as enterprise. Privian brings real AI infrastructure to the orgs the hyperscalers ignore, at a scale and price that fits.
How It Works
A short process to get to real work quickly.
Thirty minutes. You describe what you're building or fixing. We ask enough to understand the real problem, not the presented one.
A clear written summary of what we'd do, what it costs, and what you'd have at the end. No ambiguity about deliverables.
Actual work. Code written, architecture designed, system built, or advisory delivered, depending on what you hired us for.
You own what we built. Documentation, knowledge transfer, and a clear path to run it without us if that's what you want.
Recent Writing
Practitioner-level posts on AI infrastructure, agentic ops, and cloud, from Echoes of the Machine.
Test sets, golden examples, regression detection. How you find out the AI broke before a customer does, and why it has to be a permanent part of the stack.
AI · May 2026The most-edited surface in an AI product needs the same git-based, CI-tested, feature-flagged discipline as everything else.
AI · May 2026Embeddings, chunking, hybrid search, the prompt template that pulls in the right context. This is the surface that earns the bill.
Tell us what you're working on. If it's a good fit, we'll set up a 30-minute call. If it isn't, we'll tell you that too.
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