# Control the Impossible > For the complete documentation index, see [llms.txt](https://acaysia.com/llms.txt); a single-file corpus of every page is at [llms-full.txt](https://acaysia.com/llms-full.txt). Every page in that index is served as Markdown: append `.md` to its URL or send `Accept: text/markdown`. Canonical: https://acaysia.com/ Optimization for physical processes. Higher yield, lower energy, failsafe in under 100 milliseconds. Proven first on chemical reactors. [Book a discovery call](https://acaysia.com/contact.md) ## Key metrics - **>2%** — Yield Improvement - **~10%** — Energy Reduction - **<100ms** — Failsafe Response ## The problem ### You've optimized this reactor before. You'll do it again next year. Every plant has been through advanced control projects. Most have working APC on at least some loops. 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. 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. ## How it works ### Optimization that reads the process Acaysia describes your process as data, then optimizes against it in real time. The same four steps run whether the unit operation is a reactor, a column, or a dryer. #### Step 01 — Model the process Acaysia builds a model of your process from your plant data and known physics. That model is what the controller optimizes against. #### Step 02 — Optimize in real time 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. #### Step 03 — Fail safe to PID On any fault the controller hands back to your existing PID in under 100 milliseconds. You hold the safety envelope the whole time. #### Step 04 — Improve on your data Models retrain on your process history on-premises, with versioned rollback. Performance climbs without data ever leaving the plant. ## Proof ### Proven in chemical reactors Continuous stirred-tank reactors are where Acaysia runs today. The full control system runs on real reactor hardware, so the yield and energy numbers above come from a running CSTR, not from simulation. Control is handed over in stages. The system runs in shadow and advisory first, so it never gets more autonomy than it has earned. [See the deployment journey](https://acaysia.com/product.md) ## Why it generalizes ### One architecture, every unit operation 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. **Every unit operation, described the same way:** | 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 | - **Controller** — Reads the ontology. The same controller runs every unit operation. - **Ontology** — One shared description for every unit operation. - **Unit operation classes** — CSTR, Batch reactor, Plug flow reactor, Distillation column, Crystallizer, Evaporator. One ontology, one controller. Each new unit operation joins the same system. We do not rebuild the controller. ## Safety and integration ### Safe to put in a real plant Acaysia sits next to your PLC and respects every interlock it already has. The safety architecture is unit-op-agnostic by construction. The same Trust Arbiter that supervises a reactor will supervise a column or a crystallizer. #### Supervision — Trust Arbiter Every control move is checked against your limits before it reaches the plant. Anything outside the envelope is blocked. #### Fallback — PID under 100ms On any fault the controller reverts to your proven PID in under 100 milliseconds. No gap in control. #### Standards — ASIL-D inspired The safety architecture is modeled on automotive ASIL-D and is SIL compatible. It never interferes with your Safety Instrumented Systems. #### Integration — Brownfield drop-in OPC UA and EtherNet/IP connect to the PLCs you already run. IEC 62443 cybersecurity considerations throughout. No rip and replace. ## Works with the infrastructure you already have - [Siemens](https://www.siemens.com/global/en/products/automation/systems/industrial.html) - [Rockwell Automation](https://www.rockwellautomation.com/en-us.html) - [Beckhoff](https://www.beckhoff.com/en-us/) - [Schneider Electric](https://www.se.com/us/en/) - [ABB](https://new.abb.com/control-systems) - [OPC UA](https://opcfoundation.org/) ## Take on a real process with us We are taking on a small number of pilot partners through 2026 across chemicals, pharmaceuticals, and adjacent 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. [Book a discovery call](https://acaysia.com/contact.md) Partners with: [NVIDIA](https://www.nvidia.com/), [a16z speedrun](https://speedrun.a16z.com/)