Sympathy for Data lets you easily build powerful and reusable data analytics applications to help you quickly analyse image data with higher confidence for better production quality management.
Easy to get started no matter if you’re a beginner or an expert when working with data analytics tools.
Includes a Python environment with a comprehensive library of data analysis components to get you started with Sympathy for Data as well as several Enterprise Toolkits.
Extensive documentation to help you Extract, Transform and Load your data to get to the data-value faster.
Interested in the enterprise grade version of Sympathy, including support, maintenance, advanced toolkits and licensing?
Powerful image processing
Seamlessly integrate image processing into your data workflows and visualise your results for improved decision-making.
Extract image data faster
Streamline the process of extracting valuable information from images, including text, objects, and patterns to identify production risks early on to avoid costly manufacturing down-time.
Get valuable image statistics
Sympathy for Data streamlines the process of extracting valuable information from images, including text, objects, and patterns.
Here we demonstrate how we used some basic image processing tools to read an analog clock in a controlled environment without machine learning or advanced algorithms.
Automate testing & validation processes
Detect data anomalies
Quick feedback loops when analysing data
Preprocess data with Sympathy’s built-in ETL
Experiment with the intuitive node-based UI
Create better data-driven stories
Build and deploy predictive models
Easily combine data from multiple sources
An enormous library of components to help you hit the ground running.
Explore the basics of Sympathy, a powerful data analysis tool that simplifies complex workflows using configurable, interconnected nodes for seamless data processing and sharing.
Extract image data, statistics, convert images in a list into a row of features or even transform. The possibilities are endless.