Israeli Firm Deci Raises $25M For AI Efficiency

Israeli deep learning company Deci announced it raised a $25 million Series B funding round last Wednesday. The company is working to harness artificial intelligence to solve the artificial intelligence efficiency gap. 

The funding round was led by global software investor Insight Partners and was supplemented by existing investors Square Peg, Emerge, Jibe Ventures, and Fort Ross Ventures, as well as new investor ICON.

Following a $21 million Series A round announced just seven months ago, the investment brings Deci’s total capital to $55.1 million.

The company hopes to use the newly acquired funding to expand its go-to-market activities and accelerate its R&D efforts. 

Founded by Yonatan Geifman, Ph.D., Jonathan Elial, and Professor Ran El-Yaniv in 2019, Deci is working to advance deep learning and eliminate production-related bottlenecks across the AI lifecycle. The company aims to minimize the AI efficiency gap – a phenomenon in which hardware is unable to meet the increasing demands of models – which is hindering greater AI commercialization. Uninhibited deep learning-powered advancements in AI have the potential to revolutionize a wide range of industries including medicine, manufacturing, transportation, retail, and communication. 

“The growing AI efficiency gap only further highlights the importance of ‘shifting left’ – accounting for production considerations early in the development lifecycle, which can then significantly reduce the time and cost spent on fixing potential obstacles when deploying models in production,” said Yonatan Geifman, CEO and co-founder of Deci. “Deci’s deep learning development platform has a proven record of enabling companies of all sizes to do just that by providing them with the tools they need to successfully develop and deploy world-changing AI solutions – no matter the level of complexity or production environment. This funding is a vote of confidence in our work to make AI more accessible and scalable for all.”

Deci is tackling the AI efficiency gap through its deep learning platform that helps data scientists adopt a more productive development paradigm. Through the platform, AI developers can leverage hardware-aware Neural Architecture Search (NAS) to build optimized deep learning models for specific production goals. According to the company, the platform empowers superior AI performance at lower operational costs, reduced time-to-market, and new applications. The platform is powered by Deci’s proprietary AutoNAC (Automated Neural Architecture Construction) technology, an algorithmic optimization engine that allows data scientists to build deep learning models tailored for any task, data set, and target inference hardware. 

Deci aims to democratize NAS technology – a field previously confined to academia or industry giants (like Google) due to high costs. Deci recently announced the 2.0 version of its platform to continue to help enterprises build, optimize, and deploy high-quality computer vision models. 

“Having a more efficient infrastructure for AI systems can make AI products qualitatively different and better, not only cheaper and faster to run,” said Lonne Jaffe, managing director at Insight Partners and board member at Deci. “Deci’s powerful technology lets you input your AI models, data, and target hardware — whether that hardware is on the edge or in the cloud — and guides you in finding alternative models that will generate similar predictive accuracy with massively improved efficiency. We are very excited to double down on our investment in Deci, backing Yonatan and the team as they bring this critical technology to AI builders across the world.”