Automated data-analysis algorithms
State-of-the-art algorithms honed through academic research drive automated data analysis and experimental planning.
What we do
State-of-the-art algorithms honed through academic research drive automated data analysis and experimental planning.
Combining robotics and instrument control, we deliver automated experiment systems that synthesize materials and measure properties without manual work.
We use generative AI — including local AI agents — in secure environments to mine past reports and automatically draft new ones.
Solutions
Materials · Chemistry · Analytical Instruments · R&D
We develop autonomous experimentation systems that close the synthesis–measurement–analysis–planning loop, covering everything from analytical algorithms to instrument integration and control. Our first product is software for automated spectral analysis.
Data Analysis · Experimental Design · Research Infrastructure
We develop Bayesian algorithms for measurement-data analysis and optimal experimental design, and deliver them as systems researchers can use every day.
Sensing · Inspection · Paperwork · Business Systems
Shop-floor solutions built on sensing data and robotics — anomaly detection, inspection support, and report automation.
Spectroscopy · Materials Analysis · Data Analysis
Contract measurement with FT-IR, XRF, electron microscopy and more, plus Bayesian contract analysis. From sample measurement to report delivery — starting from a single request.
News

Jul 6, 2026
Bringing our automated spectral analysis and experiment-condition optimization to a co-creation with Resonac aimed at new business.

May 27, 2026
a.s.ist presented software that automatically builds statistical anomaly-detection algorithms from natural-language instructions using an AI agent, and shared results from proof-of-concept trials with three companies.

Apr 14, 2026
Try AutoStatSpectra free for 7 days — our Bayesian spectral-analysis platform. It works with XPS, FT-IR, NMR and more, automating everything from peak-count and peak-shape determination to background and noise estimation.
We will ask about your data, decision criteria, and deliverables, then propose the best analysis design and a path to production software.