Palette Edgematic transforms the ML developer's user experience in creating and analyzing edge ML pipelines using a drag and drop approach. Palette software then builds an execution pipeline with the click of a button that programs multiple processors executing on the MLSoC silicon. The Edgematic Graphical User interface (GUI) provides a no code methodology for creating edge ML designs. The Palette core software can then build and deploy this resulting code to a remotely accessible edge ML client device.

Palette Edgematic Canvas
SiMa.ai changes the entire approach to effortless ML edge development by delivering a no code, visual programming tool with Palette Edgematic. Using a canvas to graphically drag and drop models and processing elements provides a developer with a methodology to create a computer vision pipeline in minutes. Using this Evaluator Edition, Edgematic users evaluate the extensive SiMa library of ML models and application pipelines with push button compilation and deployment capability. The pipelines are built using the Model Library and pre and post processing plug-ins from the catalog in the associated window in the Edgematic Canvas. This no code capability extends to plug-ins for data sources and sinks to run data sets through actual edge devices, evaluating their KPIs, and then modifying and iterating these pipelines without detailed embedded programming.

Model Library
Palette Edgematic provides a reference library of models targeting common ML network models that are quantized, compiled, and optimized by the Edgematic compiler. Execute over 40 different models covering object detection, tracking, and classification, then evaluate their Key Performance Indicators (KPIs) in minutes on actual silicon.