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Israeli startup Deci grabs $25M to bridge efficiency gap with AI

Deci team
Image credits: Deci

Deci, an Israeli deep learning startup striving to solve the AI efficiency gap, has just grabbed $25 million in Series B funding. This financing round was led by global software investor Insight Partners with participation from existing investors Square Peg (which invested in LottieFiles and Neuron Mobility), Emerge, Jibe Ventures, and Fort Ross Ventures, and new investor ICON.

Plans to expand its presence

This round comes just seven months after Deci secured $21 million in Series A funding and it takes the total funding raised by the company to $55.1 million. The funds will be used to expand Deci’s go-to-market activities, as well as further accelerate the company’s R&D efforts.

Yonatan Geifman, CEO and co-founder of Deci said, “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.”

Lonne Jaffe, Managing Director at Insight Partners and board member at Deci said, “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.”

Uses AI to build better AI

Founded by Yonatan Geifman, Jonathan Elial, and Professor Ran El-Yaniv in 2019 in Tel Aviv. Deep learning-powered advancements in AI have led to innovations that have the potential to revolutionise services, products, and consumer applications across industries such as medicine, manufacturing, transportation, communication, and retail.

However, the AI efficiency gap has proven to be an obstacle to more widespread AI commercialisation. Deci’s deep learning platform helps data scientists eliminate the AI efficiency gap by adopting a more productive development paradigm.

With the platform powered by the proprietary AutoNAC (Automated Neural Architecture Construction) technology, AI developers can leverage hardware-aware Neural Architecture Search (NAS) to quickly build highly optimised deep learning models that are designed to meet specific production goals.

The platform empowers data scientists to deliver superior performance at a much lower operational cost (up to an 80% reduction), reduce time to market from months to weeks, and easily enables new applications on resource-constrained hardware such as mobile phones, laptops, and other edge devices.

Recently, Deci announced the launch of version 2.0 of its platform, which helps enterprises build, optimise, and deploy state-of-the-art computer vision models on any hardware and environment, including cloud, edge and mobile, with outstanding accuracy and runtime performance

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