Heavy industry isn't run by pure machine learning, nor by physics simulation alone, nor by rigid business rules. FlowMaker orchestrates all three on a sovereign, composable, real-time substrate — where the value concentrates, and where competitors are scarce.
Isolating them forces trade-offs. Combining them — rigorously — changes the industrial economics.
Each intersection maps to a concrete FlowMaker brick — deployable, composable, auditable.
Accelerate physical simulation by learning, while embedding conservation laws in the loss function. Fast, reliable, extrapolable models — ideal for real-time digital twins.
Language models grounded on the plant ontology, P&IDs, maintenance history and standards. The LLM stops hallucinating — it reasons over the contextualized graph of the plant.
Operational rules frame and validate the outputs of physical models. Human expertise becomes executable — and models stay governed by business intent.
Every FlowMaker brick runs standalone or chains into a flow — anomaly detection → semantic explanation → physical validation → automated action.
A soft sensor that combines a neural network, a mass balance and an operator rule. An agent reasoning on InfluxDB/TimescaleDB in real time, framed by process physics. An anomaly detector that explains its diagnosis through the knowledge graph. That's the FlowMaker promise — and it doesn't exist anywhere else in a unified, sovereign, on-premise offer.
Market players remain confined to a single circle of the diagram. A few cover two. None offer all three in a sovereign, composable, industrial architecture.
"FlowMaker occupies the zone that generic MLOps platforms, simulation vendors and industrial historians each leave half-empty." — Industream positioning, 2026
Robust data-driven infrastructure, but blind to process physics and without native industrial semantics. OT integration is left to the customer. Databricks · DataRobot · Dataiku
Outstanding physical mastery, but weak real-time loop and proprietary architectures. No native ML orchestration, no open semantic layer. Aspen · Siemens Simcenter · AnyLogic
Excellent at storing and visualizing real-time data. Modeling and reasoning stay out of scope — these are databases, not AI platforms. PI System · Aveva · Canary
Offerings often confined to one circle — analytics (TrendMiner), data fabric (Cognite), process optimization (Braincube). Little sovereignty, little on-premise, little real hybridization. Cognite · TrendMiner · Braincube
FlowMaker's DataBridge and DataCatalog serve equally an ML model, a physics solver or a semantic engine — on the same streams, the same tag catalog, the same governance.
On-premise architecture, Docker Swarm, NIS 2.0 / ISO 27001 / AI Act compatible. Where US platforms force the cloud, FlowMaker respects OT and European regulatory constraints.
OPC-UA, Modbus TCP, S7, MQTT, BACnet. FlowMaker speaks the plant's language without an intermediate gateway — from field sensors to LLM agents.
Every Hybrid AI decision is traceable: which model, which data, which rules, which physical constraint. Essential for OT audit and for the European AI Act.