Discovery starts
with doing the work.

It began with fraud discovery.

Behavioral Outlier Optimization was discovered while our founder was coding models for fraud discovery. A practical problem—finding behavior that deserved attention—led to a shared primitive for detection, attention, and surprise.

That insight became a direction for the company: understand behavior in its context, spend computation where it matters, and connect what a system notices to what it can do next.

Machines changed the pace.

Automated systems can observe, adapt, and act while a human is still reviewing the last event. Acting against machines requires decisions that arrive at machine speed, within boundaries the operator controls.

Research and engineering stay connected.

Our work spans information geometry, spiking neural networks, adaptive defense, and agent systems. Ideas become models, tools, and experiments. Results feed back into the next question.

Ouija, our BOOGYMAN class intrusion prevention system, brings that direction into a closed-beta evaluation program.