Where OmniPath sits, and how it gets there
One layer, one output path. Models train in the cloud, pass through a security DMZ as signed artifacts, and run inference on a ruggedized GPU at the asset site. From there OmniPath writes setpoints into the regulatory control layer — and nowhere else.
The control stack
Every element in this diagram except one is already in your station. The single filled block is ours.
- Level 4Cloud trainingRL pipelines, model registry, signed artifact store. Delivers downward into the DMZ only.
- DMZSecurity DMZOne-way, signed-boot verification, auditable.
- Level 3 — supervisory · OmniPathOmniPathSupervisory optimization — unit staging, load split, speed and pressure setpoints. Supervisory cadence of seconds to minutes. Receives signed models from the DMZ; reads process data; writes setpoints down into the regulatory layer and nowhere else.
- Level 3 — where presentExisting APC / MPCCoexists with OmniPath, or is retained as the fallback target.
- Level 2 / 1 — unchangedDCS regulatory controlPID, cascade, ratio and override, with operator HMI and historian. DeltaV, Experion PKS, CENTUM VP, System 800xA, PlantPAx. Modules execute every 100 ms to 1 s. Receives setpoints and retains full manual override.
- Level 1 — independent · unchangedProtection layerThree independent functions, none of them connected to OmniPath: the safety system (SIS, ESD, fire and gas, HIPPS); anti-surge and governor turbomachinery control, working to the surge control line with recycle; and machinery protection for vibration and temperature per API 670. Protective response is 10–50 ms. There is no write path from OmniPath.
- Level 0The processCompressors, drivers, valves, transmitters.
What OmniPath does not do
We do not modify or replace your safety instrumented system. We do not modify or replace your anti-surge controller. We do not change your surge control line. We do not write to your ESD, fire and gas, or machinery protection systems. We do not require new safety-rated hardware. We do not require the regulatory control layer to be retuned. If your incumbent controllers were removed from service, OmniPath would have nothing to write to — that is the correct relationship.
Works with your existing stack
No controller firmware changes, no I/O changes, no safety system changes.
OmniPath reads from the historian and writes setpoints through OPC UA to Emerson DeltaV, Honeywell Experion PKS, Yokogawa CENTUM VP, ABB System 800xA, and Rockwell PlantPAx. Where an existing APC or MPC layer is present, OmniPath either coexists with it or is retained above it as the fallback target — the incumbent is never removed to make room for us.
Why the compute is at the station
Edge inference is usually justified by latency. That is not the reason here — a supervisory cycle of seconds tolerates a cloud round trip easily, and edge and cloud sit within a few thousand dollars a year of each other. There are three real reasons, and they compound.
The workload is a physics solver.
A dynamic formulation — one that accounts for line pack, batch interfaces and anticipatory staging — solves the network once per rollout step, not once per candidate. An 8-unit station with line pack is roughly 4.4 TFLOP per supervisory decision. A coordinated three-station liquids line is 104 TFLOP. On a CPU those are 88 seconds and 35 minutes respectively, which does not fit inside any usable cycle.
Calibration lives in high-rate local data.
A solver is only as good as its parameters, and they drift: friction factors, fouling, wear-ring clearance, and on liquids the density and viscosity that step-change at every batch interface. Keeping them current means continuous reconciliation against 1 Hz data. At the station that data is free. Shipping it costs real money on cellular and is impractical on satellite — and a model calibrated on twenty-minute-old data is solving the wrong pipeline once a batch interface has passed.
A cloud write path is a conduit worth avoiding.
A cloud-hosted optimizer writing setpoints requires a persistent bidirectional path from the internet into Level 3, on every cycle. Under IEC 62443 that is a conduit demanding continuous justification, and it is the trusted IT-to-OT pattern the TSA pipeline directives exist to prevent. One-way signed artifact delivery is a conduit a security review can approve.
| Per supervisory decision | Edge GPU | CPU |
|---|---|---|
| Gas, 8-unit station, 20-step horizon | 0.05 s | 4.8 s |
| Gas, 8-unit + line pack, 60-step horizon | 0.9 s | 88 s |
| Liquids, 6-unit station, batch tracking, 4 h | 1.6 s | 159 s |
| Liquids, 3-station coordinated line | 21 s | ~35 min |
Scroll the table sideways for the CPU column →
The GPU is required where the stations are large and the lines are coordinated. On a two-unit station a CPU would do — and we will tell you that rather than sell you a box you do not need.
Inside one decision
Full physics enumeration over the candidate space is not affordable at any station size. Screening it with a learned model and verifying only the shortlist is — about a thousand times cheaper, and it means every setpoint that leaves the box has been checked against a real model first.
- Screen — every candidate plan evaluated on the learned world-model ensemble in one batched GPU pass. On an 8-unit station that is roughly 15,280 plans: 191 feasible staging vectors, across 8 ensemble members and 10 demand and price scenarios.
- Verify — the best five verified against the real hydraulic solver, batched across the ensemble, using parameters reconciled from local high-rate data. A candidate that fails verification is discarded.
- Clamp and write — the surviving plan is clamped to the operator band, slew-limited and watchdogged before a single setpoint reaches the regulatory layer. The verification result is logged with the action, and it is a pilot deliverable.
Cloud to edge
Training is central, inference is local, and the path between them is one-way and signed.
Cloud / AWS
- Model training (RL/ML pipelines)
- MLOps registry & CI/CD
- Secure artifact store (S3/ECR)
DMZ
- Validation & security gateway
- Compliance & monitoring checks
- Air-gapped staging for edge-ready models
- Novel signed-boot model verification
Edge
- Batched physics at the asset on an NVIDIA Jetson Orin edge GPU — thousands of candidate plans screened against a learned model, the shortlist verified against the real hydraulic solver, per supervisory decision
- Ruggedized edge compute (NVIDIA Jetson Orin class) installed in the safe-area or Division 2–rated control building, outside the classified envelope — hardware selected per site electrical area classification
- Local setpoint optimization + digital twin integration
- Continuous model reconciliation against local high-rate data — friction factors, fouling, density and viscosity — so the solver stays calibrated to the pipeline as it is today
Resilient
Ruggedized Orin hardware built for harsh industrial environments, and no dependency on connectivity in the decision path. Loss of WAN costs model updates, never optimization.
Secure & Compliant
DMZ ensures one-way, auditable, signed-boot model deployment — aligned with OT/ICS security standards.
Scalable
Cloud-to-edge MLOps enables model updates without downtime.
Standards and change management
The documentation your security review will ask for is a pilot deliverable, not an afterthought.
Deployment follows IEC 62443 zone and conduit segmentation, with the edge node in its own zone behind an authenticated one-way conduit. Setpoint-writing scope is documented for management of change under the IEC 61511 / ISA 84 safety lifecycle. Architecture is designed to sit inside operators' TSA pipeline security directive obligations.
Failure modes, MOC scope and data requirements — the controls-engineer FAQ →