The embedded machine learning development platform vendor expects to double its workforce in 2022.
Edge Impulse, the embedded machine learning developer platform vendor, has raised $34 million in a Series B funding round, tripling its valuation to $234 million. The company closed a $15 million Series A round seven months ago. So far, the startup has raised $54 million in venture funding.
The company said it plans to use the funding to double its workforce to 80 employees by the end of 2022, with emphasis on expanding its solution engineering team that supports customers. In the same timeframe, the company plans to expand its developer ecosystem to 100,000 users.
Edge Impulse’s toolchain targets machine learning projects running on embedded hardware, handling everything from ML algorithm development and training to managing proprietary datasets. Compatible target hardware includes Nvidia GPUs, MCUs from Silicon Labs, STMicroelectronics and Microchip along with specialist hardware from Eta Compute. Hardware from Texas Instruments, Syntiant and Synaptics were recently added to its roster.
“We wanted to solve the problems that normal developers and engineers working on edge compute and applying machine learning are going to face. How can we overcome those? How can we make this a successful process to make use of ML? And then how can we make sure they can deploy it in their real jobs in the industry?” Edge Impulse Co-founder and CEO Zach Shelby said in an interview.
Since its launch in 2019, nearly 30,000 developers have worked on more than 55,000 embedded machine learning projects using the Edge Impulse platform (more than 9,000 projects were added in November alone). The developer base increased four-fold in the last year, according to the company, while revenues from customers including Oura, Polycom, Advantech and NASA increased three-fold.
Edge Impulse’s software-as-a-service business model includes a free tier for individuals and hobbyists. Enterprise-level subscriptions include features like collaboration on projects, working with bigger datasets, model versioning and security. Typical projects span industrial, logistics and health-related use cases.
New features planned for the platform include application testing, allowing engineers to assess strengths and weaknesses of their ML model over and above the accuracy figure. For example, if a model misses certain types of events or generates false-positives in certain situations, post-processing parameters can help tune the way the model works.
Edge Impulse’s Series B round was led by Coatue. Coatue joins existing investors Canaan Partners, Acrew Capital, Fika Ventures, Momenta Ventures and Knollwood Investment Advisory. Coatue’s David Cahn will join the Edge Impulse board.
This article was originally published on EE Times.
Sally Ward-Foxton covers AI technology and related issues for EETimes.com and all aspects of the European industry for EE Times Europe magazine. Sally has spent more than 15 years writing about the electronics industry from London, UK. She has written for Electronic Design, ECN, Electronic Specifier: Design, Components in Electronics, and many more. She holds a Masters’ degree in Electrical and Electronic Engineering from the University of Cambridge.