SensiML Announces SensiML Analytics Toolkit Integrated with Google TensorFlow Lite

By Perry Cohen

Associate Editor

Embedded Computing Design

September 18, 2020

SensiML announced its SensiML Analytics Toolkit is now integrated with Google's TensorFlow Lite for Microcontrollers.

SensiML announced its SensiML Analytics Toolkit is now integrated with Google’s TensorFlow Lite for Microcontrollers. Developers working with Google’s TensorFlow Lite for Microcontrollers open source neural network inference engine have the ability to leverage the company’s automated data labeling and preprocessing capabilities.

SensiML’s TensoFlow Lite is a version of the TensorFlow Lite from Google, which was designed to implement machine learning models on microcontrollers and memory-limited devices.

According to the company, its SensiML Analytics Toolkit, delivers the easiest and most transparent set of developer tools for the creation and deployment of edge AI sensor algorithms for IoT devices.

Further, developers can collect and label data using the SensiML Data Capture Lab, create data pre-processing and feature engineering pipelines using the SensiML Analytics Studio, and perform classification using TensorFlow Lite for Microcontrollers.

“The integration with SensiML Analytics Studio and Google’s TensorFlow Lite for Microcontrollers provides a nice end-to-end workflow for creating IoT edge models on embedded devices,” said TensorFlow Lite for Microcontrollers product manager at Google Ian Nappier in a press release.

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Perry Cohen, associate editor for Embedded Computing Design, is responsible for web content editing and creation, podcast production, and social media efforts. Perry has been published on both local and national news platforms including (Phoenix), (Phoenix),, Cronkite News, and MLB/MiLB among others. Perry received a BA in Journalism from the Walter Cronkite School of Journalism and Mass Communications at Arizona State university.

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