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 pathEigen Control builds physics-based AI for industrial chemistry inference and GPU-native simulation, helping industrial teams see process behavior sooner and act with confidence.
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 deployment in one of North America's most important NGL fractionation hubs.
Real-time quality estimates delivered to operators and control-system workflows.
Typical visibility ahead of coincident onstream Gas Chromatograph readings for faster operating decisions.
Live quality signal enabled tighter control and a throughput increase from a 120 Mbpd fractionation baseline.
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.
The platform connects process data, optical measurements, numerical methods, and modern compute, turning complex engineering signals into decisions operators and technical teams can use.
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 pathApplied mathematics and hybridizable discontinuous Galerkin methods for accurate, scalable scientific computing.
Modern math for new hardwareScientific workloads designed for the parallel compute infrastructure reshaping modern AI.
Cluster-native architectureEigen is designed around the boundary that matters in the field: instruments and process tags in, trusted quality values and engineering decisions out.
Raman spectra, DCS tags, laboratory reference data, and operating context.
Data conditioning, signal health checks, and secure local model execution.
Physics-informed models estimate live composition, quality, and field variables.
Quality values, KPIs, advisory recommendations, and control-ready outputs.
Every model is judged by the decisions it improves, from quality and yield to throughput, energy use, uptime, engineering cycle time, and safer operation.
Live quality inference, Raman-based composition estimates, and process-control support for complex hydrocarbon systems.
Quality · yield · controlFaster simulation for carbon capture, renewable fuels, emissions, water systems, and next-generation energy assets.
Design · scale-up · riskHigh-performance flow analysis for aerodynamics, thermal systems, and engineering certification workflows.
Speed · fidelity · iterationSimulation and analytical intelligence for semiconductors, reactors, materials processing, and complex production systems.
Throughput · consistency · scaleLegacy 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.
TensorFlow and PyTorch provide access to highly optimized GPU operations and scalable execution.
Numerical schemes selected for accuracy, parallelism, and efficient solutions to demanding flow problems.
An architecture built to scale scientific computing across the same class of clusters used for AI training.
Advanced technology earns trust through rigor, integration, and clarity, not spectacle or opaque claims.
Models are developed with the physical and chemical structure of the problem in view, so predictions remain meaningful to engineers.
Software and numerical methods are designed together for edge inference, GPU execution, and modern parallel infrastructure.
The end product is not a model file. It is a dependable signal, solver, or decision workflow that fits the plant and engineering stack.
We build computational platforms for real-time industrial planning and control, where better visibility and faster engineering create measurable operating value.