SpectraSherpa
Go from raw FTIR, NIR, Raman, or UV-VIS files to a reviewable PCA result, calibrated model, or classification workflow in your browser. SpectraSherpa carries file provenance through the workflow: import files, inspect the data matrix, preprocess spectra, run chemometrics, save models, and export results.
Try the free demo
Open demo.spectrascientific.ai and create an account with access code welcome_to_spectra_sherpa. No install, no Python. Bundled spectroscopy datasets and starter templates are ready to run, so you can see a full workflow in about 10 minutes.
Choose Your Path
| Goal | Start Here |
|---|---|
| Try the hosted product quickly | 10 Minutes on SpectraSherpa Cloud |
| Run locally with your own data | 30 Minutes to Local Compute |
| Bring in a file and check provenance | Import Your First Dataset |
| Check supported file formats | Supported File Types |
| Review built capabilities and boundaries | Current Capabilities |
| Build or extend from the OSS repo | Developer Setup and Writing a Plugin Node |
What Is Built
SpectraSherpa is designed as a spectroscopy application, not only a collection of numerical routines. It combines GUI-first workflow building, transparent import provenance, spectroscopy-aware data structures, reproducible workflow graphs, chemometrics templates, model outputs, validation plots, reports, exports, NIST references, optional HITRAN/HAPI synthesis, and optional SpectroChemPy-backed vendor readers. See Current Capabilities for the full grounded scope.
Cloud and AI Assistance
Sherpa Advisor and Ambient Guidance are optional scientific assistance layers. Advisor answers questions about workflows, plots, preprocessing choices, and reports; Ambient Guidance offers contextual next-step suggestions inside the app. They are labeled aids for scientific review, not replacements for spectra, metadata, validation design, or domain judgment. See Cloud vs Local OSS for AI configuration and risk guidance, and Demo Access and Limits for public demo policy.
Scientific Foundations
SpectraSherpa builds on scientific software and data maintained by the broader community, including SpectroChemPy, NIST, HITRAN/HAPI, NumPy, SciPy, pandas, and scikit-learn. Cite upstream resources when they contribute to your analysis.