AI Production Diagnostics

Your AI works,
but not in production.

UnblockedOps uncovers the cost and security blockers keeping your AI out of production. You get a clear, prioritized plan to get past them, one your team can run on its own and keep for good, so your AI ends up where it was always supposed to be: in production, earning its keep, standing up to scrutiny.

Book your free First Look →

At least one concrete takeaway about what's blocking you. No strings.

The wall you're up against.

You can tell something is wrong. You just can't tell exactly what. That not-knowing is the wall between an AI prototype that works and a system that holds up in production. Every team hits it in a different place.

The AI demo impressed everyone. Months of real engineering later, it's still not in front of real users.
GPU and cloud spend keeps climbing, and no one can pin down which workloads on the cluster are driving it.
Every time you're close to launch, another security question about your AI agents stalls the release.
An enterprise deal is waiting on a security review, and the questionnaire asks about an AI security posture you haven't had time to build, let alone document.
Your RAG system worked well in production. Now the answer quality is sliding, and the cause is buried somewhere deep in the pipeline stack.

And it's not just you: two in three organizations have delayed or slowed a deployment over Kubernetes security concerns alone (Red Hat, 2024).

A capable team can fix almost any problem it can see clearly. So when the team stays blocked, it's not because the problem is hard. It's because the problem is hidden.

Sometimes it hides in the stack: a technical cause sitting a layer or two beneath the symptom everyone is staring at. Sometimes it hides in the language: an overloaded word like "done" that each stakeholder defines differently, so everyone agrees on the plan while expecting different things. Sometimes it hides in the minds of the people closest to the system, as a blind spot or an assumption that nobody questions anymore. A hidden problem is bound to sneak in when a team has been heads-down long enough.

My job is to make the hidden problem visible. Once your team sees it clearly, the fix is the easy part.

The other side of the wall.

Over there, the same things keep happening. The bill still arrives every month. The security questionnaire still lands in someone's inbox. Something still breaks at four on a Friday afternoon. What's different is that now you can see.

The bill reads like a list of decisions you made on purpose, and when a number moves, you know which layer moved it. The questionnaire gets answered from a document that already exists, because the posture is written down, not assumed. The Friday break gets found while it's still small, because your team sees the whole stack it lives in. Your AI is in production, real users are shaping the roadmap, and the conversations are about what to build next.

The problems didn't disappear. They lost their hiding places.

The way through.

What separates the two sides of the wall isn't effort. It's knowing exactly what's in the way. That clarity starts free and ends in your hands. The First Look gets us oriented on where the wall is. Then the Diagnostic pierces through, finding where the blockers are hiding and providing a plan to address them that makes the most of the team, time, and runway you actually have. The plan is yours to run.

Start for free

The First Look

You answer a few quick questions when you book, then we spend a focused hour on your biggest challenges and where they might be coming from. Within one business day, you get a short write-up pointing to your first move and where I'd dig next. Yours to keep, whether or not we go further.

Core engagement

The Diagnostic

A hands-on investigation of your whole stack: interviews with your engineers, inspection of your architecture, code, infrastructure, and AI systems, and a trace of your cost and security blockers down to the layers where they're actually hiding. The deliverable is a prioritized plan with a number and an owner on every fix, written so your team can act on it the day they get it.

Included, then extendable

The Follow-Through

The plan is yours to run, and you're not running it alone. For a set window after the Diagnostic, I'm on call to help your team get the plan in motion: the questions that surface, the judgment calls, the step no one's sure of. Want me alongside you longer? The Follow-Through continues as its own engagement.

The Diagnostic leaves more than a report.

The Diagnostic's value outlasts the engagement. The clarity stays with your team for good, in engineers who now see what they couldn't before.

Your team gets sharper.Working through the diagnosis with me, your engineers learn more than what they were missing. They learn how to look, so the next blocker gets caught before it can hide.
Your team ships the win.The fix is implemented by your engineers, in your stack. The credit is yours: your team did the work, and you made the call.
You pay only for what you can't already do.Your engineers can fix almost anything they can see clearly. The Diagnostic is the seeing. The fixing is work your team already owns.
You get a straight answer.Since I earn nothing from the fix, the diagnosis has no agenda except the clarity that gets you unblocked.
You're not left alone when the report lands.The Diagnostic includes a first window of follow-through, so as your team runs the plan, I'm on call for the questions that come up.

Is this for you?

The Diagnostic is built for teams running AI on Kubernetes who are stuck at or coming up against the wall. They either arrive mid-crisis or they see the wall on the horizon. Both are the right time. The Diagnostic is probably not for you if you're looking for an extra pair of hands to write code or if AI isn't on your production path yet.

Clayton Lemons, Founder

Twenty years chasing hidden problems across healthcare, government, research, and enterprise, from kernel drivers to the GPU clusters where AI runs in production today. Finding the layer where the problem hides, then putting a number and an owner on the fix, has been the whole job the entire time. More about Clayton →

Kubernetes CKA / CKAD / CKSNVIDIA Certified AI InfrastructureAzure · AWS · GCPAI · ML · Data SystemsGPU Compute & Optimization

Start with an hour.

A free, focused hour on where you're stuck. You'll leave with at least one concrete takeaway. Within a day, you'll have a short write-up: your first move, and where I'd dig next.