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
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.
InputProcess streamDCS + optical signals
InferenceEigen modelPhysics-guided
OutputLive chemistryControl ready
Raman responseComposition fingerprint
measured model
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
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
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.
First-principles modeling
Applied mathematics and hybridizable discontinuous Galerkin methods for accurate, scalable scientific computing.
Modern math for new hardwareMulti-node GPU systems
Scientific workloads designed for the parallel compute infrastructure reshaping modern AI.
Cluster-native architecture
Eigen IC Analyzer architecture
Product quality inference that closes the loop.
For distillation towers and reactors, Eigen IC Analyzer continuously learns from fresh plant data at the edge, produces high-frequency product-quality estimates, and returns those values to the DCS for closed-loop control.
Continuous learning and inference loopPlant-edge deployment
Plant and reference data
DCS tags, Raman spectra, analyzer or laboratory references, and operating context are time-aligned at the plant edge.
Continuous edge training
Fresh plant data continuously retrains candidate models at the edge. Validation and health checks govern promotion into live inference.
Infer product quality
Validated models estimate distillation and reactor product quality from live measurements, with confidence and drift tracking.
Close the loop
The inferred quality variable is written back to the DCS and used as feedback for closed-loop product-quality control.
Distillation tower inference
Reactor product quality
Continuous edge training
Closed-loop control
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.
Refining & petrochemicals
Live quality inference, Raman-based composition estimates, and process-control support for complex hydrocarbon systems.
Quality · yield · controlEnergy transition
Faster simulation for carbon capture, renewable fuels, emissions, water systems, and next-generation energy assets.
Design · scale-up · riskAerospace & mobility
High-performance flow analysis for aerodynamics, thermal systems, and engineering certification workflows.
Speed · fidelity · iterationAdvanced manufacturing
Simulation and analytical intelligence for semiconductors, reactors, materials processing, and complex production systems.
Throughput · consistency · scale
02 / Accelerated simulation
Read the platform note ↗
Modern math for modern compute.
Eigen is rebuilding scientific computing around parallel numerical methods, AI linear-algebra platforms, and multi-node GPU systems.
First-principles numerical methods
GPU-native solver architecture
Fast iteration across complex flow problems
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
Emailmail@eigencontrol.com↗
LocationHouston, Texas↗