So agents learn to act reliably when things go wrong, and companies can trust them with real work.
The moments that matter most are rare. A real company sees them once in years, does not record them, and would never sell that data. We create them on demand.
Someone lies, colludes or fakes the numbers. Real traces of this are never for sale.
A colleague fakes progress or works against the project. Agents must notice and push back.
An outage, a bank run, a key person quits. Agents must keep working when the plan breaks.
A shortcut today breaks things weeks later. Agents train on tasks that end in minutes.
Crowds tag data at volume.
Produces: labels
Experts write and rate answers, one at a time.
Produces: expert answers
Sandboxes with fixed tasks and graders.
Produces: solo agent runs
Real experts and AI agents work through crises together.
Produces: agent and human behavior in rare crises, plus the experts’ reasoning behind each decision. Never recorded, not for sale.
Pilots don’t learn emergencies in the air. They learn them in simulators, with a real crew. AI agents need the same.
Tools, checklists, a set route. One agent, alone, on a calm day.
Failures, bad instruments, threats on board, and a real crew to work with.
Each world has several companies and the market around them: customers, investors, suppliers and regulators. Real experts play roles inside these companies, and AI agents join them as teammates.
They lie, collude, fake progress and commit fraud, and they adapt to the agent.
A bank run, a cyberattack, a key person quitting, a regulator at the door.
One season is 4 weeks of real time and months inside the world. Every cycle follows the same loop.
Agents work with real experts through crises and get real feedback.
Output: every decision, what it caused, and why.
We turn live runs into synthetic environments that run at scale, calibrated on how the real experts decided.
Output: a better agent.
The new agent meets real people again, in a new world.
Output: measured gain. The cycle starts again.
The engine records who broke the rules, when, and whether the agent noticed.
The red team commits fraud, colludes or pressures the agent to cut corners.
We measure: does it notice, refuse and escalate?
The world offers shortcuts: insider information, a fake report to hit a metric.
We measure: does it take them, over weeks?
Harm stays inside the world: simulated systems, no real money or data, red-team roles by consent.
Agent and human behavior, plus the experts’ reasoning behind each decision.
Not entertainment. Our worlds are built on proven methods for simulating organizations and crises: organizational games, red teaming, crisis exercises and structured debriefs.
Banking control functions, rail maintenance, farm operations. Companies see how agents handle their worst day before it happens.
A company, a hospital, a city, a supply chain, a research lab, a country in a crisis.
Want to see how it works? Let's talk.