Physics-based industrial AI

See the process. Control the outcome.

Eigen Control builds physics-based AI for industrial chemistry inference and GPU-native simulation, helping industrial teams see process behavior sooner and act with confidence.

Built for real-time industrial operations Physics-guided models Engineered in Houston
Live process model
14:32:18 CST
InputProcess streamDCS + optical signals
InferenceEigen modelPhysics-guided
OutputLive chemistryControl ready
Raman responseComposition fingerprint
measured model
40090014001900 cm⁻¹
Quality index98.7inside target
Model confidence99.2%stable
Update interval1.0 scontinuous
Illustrative interface · not operating data
QUALITY SIGNAL · CONTROL READY
Industrial proof

Proven in live NGL fractionation

Eigen IC Analyzer delivered real-time product-quality inference inside a major Mt. Belvieu NGL fractionation operation. Live composition estimates were delivered to operators and control systems at high frequency, ahead of traditional analyzer cycles, supporting quality visibility, control stability, and operational decision-making.

Industrial AI is not a dashboard. It is a live quality signal in the control room.
Deployment environment Major Mt. Belvieu NGL operator

Industrial deployment in one of North America's most important NGL fractionation hubs.

Measurement speed Every 10 seconds

Real-time quality estimates delivered to operators and control-system workflows.

Analyzer advantage 10-20 minutes

Typical visibility ahead of coincident onstream Gas Chromatograph readings for faster operating decisions.

Control impact 5% higher throughput

Live quality signal enabled tighter control and a throughput increase from a 120 Mbpd fractionation baseline.

Computational intelligence for high-consequence engineering and operations.
Refining
Energy transition
Aerospace
Advanced manufacturing
Preparing Fourier sketch
Fourier illustration

Math-driven process control.

AI discovers the math.

A refinery's eigenfrequencies are where control starts: Fourier methods separate the modes moving through the process and turn them into variables a controller can act on.

Setpoint Control frequency circle Mode trace
CFD demonstration

Fluid dynamics, accelerated.

One industrial intelligence layer

From live chemistry to faster simulation.

The platform connects process data, optical measurements, numerical methods, and modern compute, turning complex engineering signals into decisions operators and technical teams can use.

01 / PROCESS INTELLIGENCE

Eigen IC Analyzer

Real-time quality inference from process signals. Build reliable chemistry estimates for monitoring, advisory control, and closed-loop applications without waiting on delayed laboratory results.

Industrial deployment path
02 / NUMERICS

First-principles modeling

Applied mathematics and hybridizable discontinuous Galerkin methods for accurate, scalable scientific computing.

Modern math for new hardware
03 / SCALE

Multi-node GPU systems

Scientific workloads designed for the parallel compute infrastructure reshaping modern AI.

Cluster-native architecture
Plant-ready architecture

Intelligence built for the operating environment.

Eigen is designed around the boundary that matters in the field: instruments and process tags in, trusted quality values and engineering decisions out.

Industrial inference pathEdge or enterprise deployment

Signals

Raman spectra, DCS tags, laboratory reference data, and operating context.

RamanOPC / DCSHistorian

Edge compute

Data conditioning, signal health checks, and secure local model execution.

ValidationPreprocessMonitoring

AI inference

Physics-informed models estimate live composition, quality, and field variables.

PredictionConfidenceDrift

Operational value

Quality values, KPIs, advisory recommendations, and control-ready outputs.

DCSDashboardControl
ContinuousLive process visibility
ExplainableSignals with engineering context
MonitoredHealth, confidence, and drift
IntegratedOutputs where teams already work
Applications

Technical capability tied to operating value.

Every model is judged by the decisions it improves, from quality and yield to throughput, energy use, uptime, engineering cycle time, and safer operation.

01

Refining & petrochemicals

Live quality inference, Raman-based composition estimates, and process-control support for complex hydrocarbon systems.

Quality · yield · control
02

Energy transition

Faster simulation for carbon capture, renewable fuels, emissions, water systems, and next-generation energy assets.

Design · scale-up · risk
03

Aerospace & mobility

High-performance flow analysis for aerodynamics, thermal systems, and engineering certification workflows.

Speed · fidelity · iteration
04

Advanced manufacturing

Simulation and analytical intelligence for semiconductors, reactors, materials processing, and complex production systems.

Throughput · consistency · scale
Next-generation CFD

Modern math for modern compute.

Legacy CFD software was shaped by earlier hardware limits. Eigen is rebuilding the solver stack around AI linear-algebra platforms, parallel numerical methods, and multi-node GPU systems.

01
AI platforms as linear-algebra engines

TensorFlow and PyTorch provide access to highly optimized GPU operations and scalable execution.

02
Hybridizable discontinuous Galerkin methods

Numerical schemes selected for accuracy, parallelism, and efficient solutions to demanding flow problems.

03
Multi-node by design

An architecture built to scale scientific computing across the same class of clusters used for AI training.

Read the CFD platform note
Eigen solver / flow field● CONVERGING
Residual2.7e−08decreasing
GPU occupancy94.1%balanced
Mesh cells8.4Mdistributed
Nodes08synchronized
Illustrative solver view · not benchmark data
Engineering principles

Built for demanding operating environments.

Advanced technology earns trust through rigor, integration, and clarity, not spectacle or opaque claims.

First-principles grounding

Models are developed with the physical and chemical structure of the problem in view, so predictions remain meaningful to engineers.

Compute-native architecture

Software and numerical methods are designed together for edge inference, GPU execution, and modern parallel infrastructure.

Operational integration

The end product is not a model file. It is a dependable signal, solver, or decision workflow that fits the plant and engineering stack.

Eigen Control

AI grounded in first principles for real industrial systems.

We build computational platforms for real-time industrial planning and control, where better visibility and faster engineering create measurable operating value.

Start a technical conversation

Bring us the process, signal, or simulation bottleneck.

Emailmail@eigencontrol.com LocationHouston, Texas