Services

Fix the bottleneck, not the buzzword.

I find where your business actually loses time and money, then build the system that ends it. Framed around where AI projects break — not a menu of acronyms.

The method

Three moves, in order.

Diagnose before you build; prove after. The sequence is the product — it’s what keeps a project from shipping a confident answer to the wrong problem.

01 / Diagnose

Find & fix the process

  • Process discovery & optimization
  • Advisory — "do you actually need AI?"
  • Locating the broken layer before any code
02 / Build

Build the system

  • Custom AI agents
  • AI process automation
  • Deterministic process automation
  • Optimization engines (operations research)
  • Mobile forms & field-ops development
03 / Prove

Integrate & prove

  • Software & platform integration
  • Data contracts & governed AI access (MCP)
  • Validation & measurement — a decision, not a dashboard

What I do

What that looks like in practice.

01

Process discovery & optimization

The problemHalf of what gets called an “AI problem” is a process problem in disguise — undocumented handoffs, exceptions nobody tracks, a workflow that only lives in people’s heads.

What I buildI map what actually happens — every step, owner, and exception — and locate the broken layer before any code. Sometimes the deliverable is a model. Often it’s a process change worth more than one.

Why orchestration won’t fix a broken process →
02

Integration & data contracts

The problemAgents act on the 20% that’s structured. The 80% that matters — contracts, email threads, policy docs — lives in systems that don’t talk. The integration nobody owns is where the work stalls.

What I buildI build the seams: software and platform integration, and the data contracts that define what passes between systems. A Salesforce ↔ ServiceTitan ↔ NetSuite pipeline on AWS is the kind of thing — not a demo, a load-bearing integration.

When a carrier exposes its stack as an API →
03

Automation that removes steps

The problemA faster dashboard isn’t ROI. Automation earns its keep when it deletes a step a human used to do — and only then.

What I buildCustom AI agents, AI process automation, deterministic automation, operations-research optimization engines, and mobile forms for field ops. I pick the lightest tool that removes the step — a model, a solver, or a plain rule.

The scheduler no product could build →
04

AI governance & safe rollout

The problemMost enterprise AI runs outside any governance. Deploy without containment and you haven’t deployed an agent — you’ve deployed an incident with a delay.

What I buildScoped access, kill switches, audit trails, and an MCP layer that gives agents governed access to enterprise data. Roll out AI you can actually see, and stop.

Shadow AI is an inventory gap →

Tell me what’s broken. Or let me find it.

Know your bottleneck or just feel it — either way, I’ll find the fix. If you don’t need AI, I’ll tell you that too.

Open to contract AI-automation engagements across the US — on-site, hybrid, or remote.