Shapelets is a comprehensive data science framework to manage the data, from the early stages (collection, ingestion, storage) through its value extraction (preparation, visualization). It allows for transforming and empowering companies toward data-driven models.

Designed and engineered to help data science teams better monitor the data feeds in real-time, using machine learning to automate tasks and provide recommendations when needed. An all-in-one tool that offers a solution at every step of the data processing cycle.

Being a software tool, it can be deployed on local computers, in the cloud, and in on-premise infrastructures. It provides its storage engine, optimized for time series and connectable with most data stores, including common streaming data services. As per processing capabilities, it incorporates highly efficient implementations of state-of-the-art algorithms for prediction, classification, and anomaly detection in time series, while keeping users free to use their favorite python libraries or even their own code implementations, that can be seamlessly deployed in computing clusters to obtain the highest performance through distributed executions.

It is unique to the market, capable of managing and modeling a vast amount of time series data, and visualizing them in an easy and intuitive way, thereby capturing information that is relevant for the various departments in a business, third parties, data professionals, etc. All in real-time.