Reveal the Unseen.

ScryLab is designed for rapid analysis and comparison of technical measurement and simulation data – particularly in the time and frequency domain up to the megahertz range. If you want to understand, manipulate, and directly compare physical signals without building your own scripting environment, this tool is well-suited. ScryLab is less suitable for extensive statistical evaluations, data science workflows, reporting, or complex database structures. The focus is clearly on interactive, signal-based analysis and gaining physical insights.

While many established programs offer very extensive feature sets and sometimes include their own scripting or automation logic, ScryLab focuses on a streamlined, direct approach. The application integrates into existing workflows and enables intuitive manipulation, comparison, and step-by-step evaluation of physical signals. Signal operations remain editable, results are immediately visible, and navigation and zooming are continuous without disruptive interaction. The goal is a simple, transparent analysis environment that supports physical understanding – not a second development platform within the existing toolchain.

The application is designed for time- and frequency-based signals in the range from approximately 1 Hz to the megahertz range. Supported types include: time series, frequency spectra, spectrograms, transfer functions, non-monotonic XY data. It is particularly suitable for high-frequency measurement and simulation data from technical systems where performance and direct comparability are crucial.

After license activation (once per year), no internet connection is required. This allows ScryLab to be used flexibly outside of a fixed workplace, for example during vehicle or aircraft testing.

ScryLab is cross-platform and runs on both Linux and Windows.

The goal of development was to make data analysis as simple and intuitive as possible. The name ScryLab combines "scrying" – an ancient method of predicting the future by observing reflections – with "Lab" for laboratory. Together, they represent the vision of making hidden insights in data visible: Reveal the Unseen.