SHAPELETS FLOW
STORAGE STREAMING FOR
TIME-SERIES

With Shapelets you can develop your own algorithms, integrate them with our algorithms and publish them within Shapelets in a distributed manner in less than a minute

AN ALL INCLUSIVE PLATFORM
FOR DATA SCIENTISTS

Shapelets Flow is a distributed lambda architecture that captures custom algorithms and analytical flows and combines any Python library (TensorFlow, Keras, NumPy…) with Shapelets algorithms

Shapelets Flow is a distributed lambda architecture that captures custom algorithms and analytical flows and combines any Python library (TensorFlow, Keras, NumPy…) with Shapelets algorithms.

Extensibility

New algorithms can be added and used by any major language through the DSL frontend, regardless of its implementation language.

Integration

Each worker uses native libraries (NumPy, Pandas...) allowing full composition with existing solutions. Use Jupyter Notebooks, Flask, Stream lit or any of your preferred environment without constraints.

Simple Deployment

When new algorithms are ready, you can publish straight to our data apps or your favourite BI tool. Users can quickly solve business problems reducing the cost of deployment to zero.