Material Intelligence.
Operationalized.
We turn hyperspectral imagery into explainable material intelligence for higher recovery on the line, clearer decisions from orbit, and defensible reporting in the field.
Already evaluating? Request a Material Test or Discuss Your EO Use Case.
One Platform. Three Operational Outcomes.
The same platform can sort polymers on a conveyor, map surface mineralogy from orbit, and trace atmospheric plumes across industrial infrastructure. Different environments, same advantage: explainable decisions from spectral data.
We quantify recovery improvement on your actual material stream during evaluation.
We show how much review time your team can save on a real area of interest.
We validate supported plume-detection performance for the monitoring workflow in scope.
Recover More
Valuable Material.
Identify complex polymers and hard-to-sort materials at operational speeds, then validate the business case with your actual samples, line conditions, and recovery targets.
Validated on real MRF streams and industrial feedstock.
Request a Material Test
Turn Orbital Data
into Actionable Intelligence.
Detect, classify, and monitor material signatures across large geospatial environments without forcing your team to build a custom hyperspectral pipeline from scratch.
Tested across satellite and airborne hyperspectral datasets.
The platform powering
Material Intelligence.
Reduce the data burden, run operational inference in the right environment, and deliver outputs that technical teams can evaluate with confidence.
Explore the TechnologyTrain models on your data
Deploy to edge or cloud
Generate explainable outputs for decisions
One platform, one main view, and a clearer sense of how teams move from analysis to inspectable output.
Compression
Reduce the cost and friction of moving large spectral datasets through production pipelines.
Compute
Run inference in the environment that matches the operational workflow.
Explainability
Give technical teams outputs they can inspect, review, and trust.
Built to move from evaluation into production.
High-dimensional data processing, deployable inference, and evaluation structure for industrial and geospatial applications.
Operational deployment
Designed for environments where throughput, reliability, and deployment constraints directly affect commercial outcomes.
Run in environments where low latency and stable processing are operational requirements.
Fit within existing industrial and geospatial workflows instead of forcing a greenfield reset.
Data fit
Support heterogeneous spectral and geospatial inputs across different operating environments.
Trust
Give evaluators outputs they can inspect, compare, and use as part of a real decision workflow.
Evaluation path
Start with a material test or EO scoping conversation tied to the user's actual data and operating environment.
Explore TechnologyResources
Surface proof material that helps buyers evaluate the category, the workflow fit, and the platform.
Turning One Reference Spectrum Into Full-Scene Target...
See how a CNN-based single-spectrum detector trained on Clarity outperformed classical baselines on full-scene MUUFL target detection across multiple train-test scene pairs.
Lithium Detection over the McDermitt Deposit Using...
Lithium detection pipeline at the McDermitt deposit using EnMAP hyperspectral data and Metaspectral’s Clarity analysis platform.
Repeatable Hyperspectral AI Workflows
Hyperspectral teams do not just need faster answers. They need a way to preserve analyst judgment, encode review logic, and apply the right process consistently across scenes, sensors, and operators. That is where workflow-based AI changes the equation.
Test your material. Scope your project.
Start with a scoped evaluation on your data, your environment, and the decisions you need to make.