The Maze AI Operating System
Six steps from a manual operation to a system that holds up in production. Each step produces something you can check. Hover any step to read it.
Discovery from first principles
If you rebuilt this operation today, knowing what AI can do, how would you do it? We start there, not from the org chart you already have.
What each step produces.
Discovery from first principles
If you rebuilt this operation today, knowing what AI can do, how would you do it? We start there, not from the org chart you already have.
Codify the business logic
SOPs, decision trees, and KPIs go into a spec. The rules that live in three people's heads become something a system can run.
Build on a deterministic harness
Event-driven workflows do the heavy lifting. The model runs only where it earns its place, never as the thing holding the wiring together.
Personify with internal AI employees
Each agent gets a name, a job, and a boundary. Your team knows who does what, and so does the audit log.
Verify with hard success criteria
Success is a KPI checklist agreed up front, not the model reporting that it went well. If it does not clear the bar, it does not ship.
Close the loop
Monitoring, retraining, and periodic re-architecture. The system that was right in March is reviewed in September, before it drifts.
We sell relief, not technology.
Most AI pilots die before production. Not because the model is wrong. Because nobody defined what success was supposed to look like, and the thing was held together by a prompt.
We start from the operation, map the rules that live in three people's heads, and build the boring part on a deterministic harness. The model earns its place where it actually helps, and nowhere else.
Then we tie it to a number. Hours back, dollars saved, error rate down. If it does not move the number, it was not worth building.
The ones we get most.
Both, in order. The Audit and Blueprint map and design. The Build ships the system. The Partnership runs it. You can stop after any step.
As little as possible runs on a model. Event-driven workflows do the deterministic work. The model is used only where judgment or language is genuinely needed, behind clear inputs and outputs.
We agree the success criteria before we build: a KPI checklist tied to the P&L. If the system does not clear the bar, it does not ship. That is step five, not an afterthought.
Start with the number.
The Audit maps your operation, ranks the builds with a clear line to the P&L, and tells you what each is worth. Then you decide.