Edge Impulse, a TNW community member that produces an AI platform for developers, has been acquired by American chip giant Qualcomm for an undisclosed sum.
Qualcomm said it had bought Edge Impulse to boost its machine learning software capabilities, particularly for its Dragonwing line of AI-powered chips.
Nakul Duggal, Qualcomm’s head of IoT, said the acquisition would strengthen his firm’s “leadership in AI” and bolster “critical sectors such as retail, security, energy and utilities, supply chain management, and asset management.”
Under the deal, Edge Impulse will integrate its operations with Qualcomm’s, but maintain its own offices, employees, and website.
“Our team and mission remain the same, only now, we will have even more opportunities and capabilities to accelerate what we do best,” said Zach Shelby, Edge Impulse’s co-founder and CEO.
Shelby, an engineer and entrepreneur from Finland, founded Edge Impulse in 2019 alongside Dutchman Jan Jongboom. The pair met while working on IoT systems at British chip firm Arm.
At Edge Impulse, Shelby and Jongboom built a platform the slashes the time it takes to create machine learning models for small devices such as sensors, microcontrollers, and cameras.
Shelby said the team had identified a big gap in the market.
“Recognising that the compute capabilities of microcontrollers had grown to the point where they were able to run domain-specific AI models directly onboard, we realised there were an endless number of use cases that would benefit from moving AI from the cloud to the edge,” he wrote in a blog post.
Edge Impulse has raised $54.3mn to date. In 2021, the company bagged $34mn in Series B funding at a valuation of $234mn. Two years later, it reported revenues of $14.7mn. Its platform is currently used by over 170,000 developers to create, deploy, and monitor AI models on the edge.
Shelby credited the platform’s popularity to helping developers eliminate laborious and manual tasks when setting up AI in edge devices.
“Edge Impulse gives developers a tool that automates data collection, simplifies model training, provides advanced optimisation tools, and offers one-click deployment to many types of hardware, from MCUs to CPUs, GPUs, and NPUs,” he said.
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