Your Own AI Engineering Team. Inside Your Infrastructure. Not Mine.

I install a private, multi-agent AI system — the same one running this website — inside your AWS, Azure, or on-prem environment, authenticated through your own identity provider. Your code never leaves your walls.

The Problem

AI App Builders Are Fast. They're Also a Liability.

  • Every popular AI app builder runs your code through someone else's cloud, someone else's session, someone else's security posture
  • They're built to produce a convincing demo, not to survive a security review
  • When you outgrow one, the usual answer is "rebuild from scratch" — not migrate
  • None of that works if you have real customer data or a compliance requirement

Independent security scans of production apps built this way have found the majority carrying real issues — exposed secrets, exposed customer data — because speed to demo and safety in production are different problems. (Cloud Security Alliance research note)

The Fix

A Private AI Engineering System, Not a Shared One

Not a text box that generates a demo. A persistent team of AI agents that read, write, test, and deploy code across your own repos — installed inside your environment, not a vendor's.

  1. Multi-agent — more than one chat session. A standing system that can carry work across repos and over time.
  2. Git-native — every change is a real commit. Reviewable, revertible, not locked in a proprietary file format.
  3. Yours — runs in your AWS, Azure, or on-prem, authenticated through your own identity provider. Nothing leaves your perimeter.
Proof, Not a Pitch Deck

This Isn't a Concept. It's Running Two Production Sites Right Now.

This website and fieldmappings.com are both built, maintained, and deployed entirely through this exact system — multi-agent, git-native, running on my own infrastructure. When you talk to me, you're talking to someone using the thing he's selling, every day, not presenting a slide about it.

I'm not asking you to be the first company to try this idea. I'm asking you to be among the first to run it inside your own walls.

How It Works

Three Steps. No Long Discovery Phase.

  1. Discovery call — We look at your environment, your identity provider, and the first real problem worth solving.
  2. Install — The system goes into your AWS, Azure, or on-prem environment, wired to your git and your CI/CD.
  3. Build — Your team works with the agents directly, in the tools you already use, to ship real internal tools.
Who It's For

Good Fit

  • You have real production systems and real compliance/security requirements
  • You've tried (or considered) an AI app builder and hit its limits
  • You want your team building real internal tools, not just demos
  • You're comfortable being an early design partner, not buying a mature category leader

Not a Fit

  • You want a public self-serve signup today, no conversation
  • You need a battle-tested platform with a long reference list — not yet, that's coming
  • You can't grant install access into your own cloud or on-prem environment
  • You're looking for a no-code tool for a non-technical solo project
Why This Exists

25 Years of Fixing What Others Said Was Too Complex

From aerospace engineering at NASA to complex platform modernization across retail, insurance, healthcare, and logistics, I've spent my career replacing fragile systems for companies like The Home Depot and GameStop. This system is what I built for myself to do that work faster — and it's now what I run my own sites on.

I'm not a platform company with a sales team. I'm one engineer who will personally install this in your environment and work with your team directly.

Early Access

Book a Discovery Call

Pick a day and time that works for you. I'll confirm by email — no scheduling account, no third-party calendar tool holding your info.