TEM-SEM EDS Quantitative Analytics
Quantify the Structure and
Elemental Composition
for ALL Images
Curate Your Data for Materials GenAI
Leave no image underanalyzed, ever again.
More images and more data mean faster, better insights. Segment and quantify the structure and elemental composition of every feature, in every image.
You've spent years collecting SEM, TEM, and EDS data: millions of images, trillions of features. Unlock your data to drive performance, improve reliability, increase yields, and accelerate innovation.
Know your data, choose your future.
Custom Segmentation
Combine custom and human-driven ML segmentation along with spectral processing to quantify the elemental composition and structure of every feature in every image.
Quantification
Advanced algorithms reveal every pixel: precise identification and location with 50-100X higher resolution than traditional methods.
- Every pixel, feature, and image
- 10, 10K, or 10M+ images
Curation
Guaranteed pixel-level traceability and provenance of image and processing parameters ensure your data can be accessed and leveraged as needed.
Scorecards
Quantitative Scorecards deliver clarity and control:
- Compare processes, materials, and machines
- Reveal hidden patterns and variations
- Workforce skills development
- Track performance trends over time
- Empower teams with actionable intelligence
Insights
Unlock existing materials data for:
- Performance benchmarking across operations.
- Root cause analysis
- In-line & predictive quality control
- Innovation acceleration with data
- Intelligent automated continuous improvement
Statistical Analytics
Accurate and precise, statistically valid data with the highest confidence (lowest p-value) for:
- Technology development
- Manufacturing processes
- Failure Analysis
Materials GenAI
Transform image and process data into nano-scale materials intelligence powering GenAI to predict performance, improve yields and reliability, reduce costs, and accelerate new product development.
AI-ready, optimized data formats for:
- Large Language Model (LLM) training
- Retrieval-augmented generation (RAG)
- Materials AI Agents