Create compact algorithms that execute on tiny IoT endpoints,
not in the cloud
Collect accurate, traceable, version controlled datasets
Utilize advanced AutoML code-gen to quickly produce autonomous working device code
Choose your interface, level of AI expertise, and retain full access to every aspect of your algorithm
Build edge tuning models that that customize behavior as they see more data.
SensiML Analytics Toolkit suite automates each step of the process for creating optimized AI IoT sensor recognition code. The overall workflow uses a growing library of advanced ML and AI algorithms to generate code that can learn from new data either the development phase or once deployed.
July 1, 2021 – About six months ago we, the folks at QuickLogic, and the Avnet Hackster.io online community announced our Challenge Climate Change contest. There were so many amazing tinyML solutions addressing climate change that it was difficult for our panel of judges to select the very best. However, six ideas rose to the top (three in the "battery powered" category and three in the "line powered" category).See Winners
June 29, 2021 – Microchip’s microcontrollers are used all over the world in a broad range of sensor-based applications. Learn how SensiML's partnership with Microchip enables an automated design flow in which the SensiML tools can easily tap into sensor data from the MPLAB X IDE to build models small enough to span Microchip's MCU product line.More Info
May 10, 2021 – SensiML announces it has launched an Open Source Initiative to accelerate the adoption of TinyML smart sensing IoT applications. The initiative builds upon SensiML’s existing efforts to design flexibility, transparency and efficiency into its product suite by giving developers control and insight over vital aspects of their ML workflow, tools, data, and resulting models.More Info