Accelerating development of smart systems with breakthrough edge-native AI

MicroAI has announced MicroAI Launchpad, a quick start development and deployment tool. It helps organisations simplify and accelerate the design, development, testing, and deployment of next-generation smart systems that run embedded MicroAI software on MCUs and MPUs in edge and endpoint devices.

Launchpad makes it easy to handle customers with SIMs worldwide and offers a flexible way to manage and reconfigure device profiles. It gives engineers a single pane of glass for customisable dashboards, comprising account creation, authentication, credit card billing for global SIM connectivity, mobile SIM or LoRaWAN connectivity activation, and easy onboarding of its embedded software libraries.

“MicroAI’s goal is to democratise the development of smart machines for all organisations across any industry,” said MicroAI CEO, Yasser Khan. “Regardless of industry or product, building a next-generation smart device includes creating an edge AI model, but also integrating connectivity and cloud resources, as well as device activation and management.”

Its embedded software, AtomML, allows OEMs to deploy personalised, edge-native AI models, with no need to develop static edge-AI models first in a cloud or laptop and then port them to the embedded device. Instead, AtomML moves the training and inferencing straight to the embedded device. It then simplifies and decreases the time and cost to integrate the MCU and MPUs into an edge device, which may be tested and scaled to POCs for mass deployment.

Launchpad, which can be white-labelled, is employed by semiconductor companies, OEMs, and service providers. Semiconductor companies that provide SKUs with the company's embedded AI software can use its end-to-end device management and provide it to their customers to assist in expediting design, development, testing and deployment. Furthermore, OEMs directly engaged with it benefit from Launchpad’s flexibility to appraise various hardware, software, and cloud solutions before finalising a deployment model. For IoT service providers, it will satisfy their requirement for a one-stop-shop for device certification, connectivity, and deployment, therefore, gaining a deeper insight view of connected devices on their networks.