Every “let’s use AI at work” project I’ve ever seen stalls in the same place: waiting for access to real company data. Everyone agrees the idea is good, and then the whole team sits around for six weeks while security reviews who’s allowed to touch what.

So we stopped waiting. We built a fake company instead.

The idea

We created a pretend business — with pretend employees, pretend systems, and pretend documents — that behaves exactly like a real company’s software would, down to the tiniest technical detail. To any AI tool trying to use it, it’s indistinguishable from the real thing. But because none of it is real, there’s nothing to leak, and nothing to wait weeks for permission to touch.

This week we added two new pieces to that pretend company:

  • A stand-in for the kind of big enterprise software (like SAP) that runs company finances and operations — with fake plants, fake business units, and fake company codes, all behaving exactly like the real software would.
  • A stand-in for a company’s internal document library — a project charter, a team directory with who owns what, an escalation plan for when something breaks, and a rollout plan.

The company is called Meridian Manufacturing Group. The project is called Project Phoenix. Neither exists. Every name, department, and detail in it is made up — which is exactly why we’re able to share all of it freely, with no approval process required.

What we built on top of it

Using that fake company as the foundation, we built the kind of AI assistant every large project eventually asks for — one you can ask things like: “Who’s responsible for this part of the project?” or “I’ve hit a blocker — who do I escalate this to, and who’s their backup?”

It reads through all the documents, understands how they relate to each other, and answers questions by citing exactly where it found the answer — which document, which section, and a link back to it. Ask it an escalation question, and it correctly pulls from two different documents to give you one clear answer, with every fact traceable back to its source.

Here’s the part that actually matters: the same AI assistant can be pointed at a real company’s real systems with zero changes to how it works — just a different address to look at. The pretend version isn’t a mockup of the real thing. It’s a full working rehearsal for it. Going from “demo” to “actually useful at a real company” is just a matter of pointing it at the real data once you have permission.

Why build it this way?

Because it turns the hardest part of an AI project — getting safe, realistic data to build against — into something anyone can just download and use:

  • Anyone can copy it and make their own version — swap in your own industry’s details in an afternoon.
  • Every version is saved and traceable — nothing about a demo mysteriously changes or disappears.
  • It costs nothing to keep running — there’s no server to maintain, patch, or pay for.
  • It’s inherently safe — because it’s fake from the ground up, there’s nothing sensitive to protect, so security sign-off takes minutes instead of weeks.

The fun part

Once this is connected into a company’s everyday chat tools (like Microsoft Teams), updating the AI assistant’s knowledge takes effect instantly — no waiting for a technical redeployment. You can tweak how it answers and watch it change in real time, in front of the actual people who’ll use it. That immediate feedback loop is what makes the whole thing worth doing.

Build a pretend company, point an AI assistant at it, and stop waiting on permission to start proving an idea works.

That same instinct — build something that can just get to work instead of waiting around for a person — is what led to The Personless Harness.

Everything described here is public and freely available. All the company data is entirely made up — any resemblance to a real company is coincidental.