AcaysiaDRT · spatial study
Your dryer, resolved before we touch a setpoint.
A DRT spatial study runs your own equipment’s geometry on a GPU. No plant data needed, nothing written to the plant.
Explore AcaysiaDRTD3Q19 LBM · nL–100s L
Real-time AI control layer
Built for any process, in any plant
Acaysia is the real-time AI control layer for industrial processes: higher yield, lower energy, and a failsafe back to your PID in under 100 milliseconds.
The problem
9 to 18 months per project, then drift
Only the highest-value plants ever got APC. The problem isn’t that optimization doesn’t exist. It’s that it doesn’t compose.
Each project rebuilds the same primitives. The model is bespoke. The controller doesn’t transfer. The improvement decays as the process drifts. Nine to eighteen months and several million dollars later, you have a slightly better version of what you started with, and the next reactor needs its own project from scratch.
A lot is being left on the table.
The controller
MPPI · model predictive path integral control
Acaysia describes your process as data, then optimizes against it in real time.
How it works
Reactor · column · dryer
The same four steps run whether the unit operation is a reactor, a column, or a dryer.
Acaysia builds a model of your process from your plant data and known physics. That model is what the controller optimizes against.
Every cycle, the controller simulates thousands of control trajectories on the model and picks the best. This is MPPI, model predictive path integral control. It optimizes for yield, energy, and throughput inside your limits.
On any fault the controller hands back to your existing PID in under 100 milliseconds. You hold the safety envelope the whole time.
Models retrain on your process history on-premises, with versioned rollback. Performance climbs without data ever leaving the plant.
Real-time optimization
Intelligent, adaptive control
The controller re-plans every cycle against a model that keeps learning from your plant, so performance climbs instead of decaying as the process drifts.
Footage · settling tanks, top-down
Why it generalizes
One ontology, one controller
PID controls every process in every industry because it runs on one generic idea, an error signal. Acaysia works the same way. It runs on a generic description of a process, so a new unit operation is not a new project. You describe it the same way as a reactor, and the same controller runs it.
Each new unit operation joins the same system. We do not rebuild the controller.
| Aspect | Example |
|---|---|
| What has to balance | Mass and energy, in and out |
| Where it connects | Feeds, products, and utilities |
| What you measure | Temperature, pressure, level |
| What you control | Flows, valves, heating and cooling |
AcaysiaDRT · spatial study
A DRT spatial study runs your own equipment’s geometry on a GPU. No plant data needed, nothing written to the plant.
Explore AcaysiaDRTD3Q19 LBM · nL–100s L
Safety and integration
Next to your PLC, inside your interlocks
Acaysia sits next to your PLC and respects every interlock it already has. The same Trust Arbiter that supervises a reactor will supervise a column or a crystallizer.
Outside your limits
Blocked before it reaches the plant
On any fault
Your PID takes over · < 100 ms
Works with the infrastructure you already have
A small number of pilot partners
Chemicals · pharmaceuticals · process industries
We are taking on a small number of pilot partners through 2026 across the process industries. If you operate reactors, columns, or other continuous or batch unit operations and want to evaluate Acaysia on a real process, talk to us.
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