Deci Secures $25 Million in Funding Round to Bridge the AI Efficiency Gap

Deci, the deep learning company harnessing AI to solve the AI efficiency gap, announced it has raised $25 million in a Series B funding round, enabling the company to expand its go-to-market activities, as well as further accelerate the company’s R&D efforts.

The funding round was led by global software investor Insight Partners, with participation from existing investors Square Peg, Emerge, Jibe Ventures, and Fort Ross Ventures, as well as new investor ICON. The investment comes just seven months after Deci secured $21 million in Series A funding, also led by Insight Partners, bringing Deci’s total funding to $55.1 million.

Deci’s deep learning platform helps data scientists eliminate the AI efficiency gap by adopting a more productive development paradigm. With the platform, AI developers can leverage hardware-aware Neural Architecture Search (NAS) to quickly build highly optimized deep learning models that are designed to meet specific production goals.

"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."

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, according to the vendor.

Deci’s deep learning development platform is powered by Deci’s proprietary AutoNAC (Automated Neural Architecture Construction) technology, an algorithmic optimization engine that empowers data scientists to build best-in-class deep learning models that are tailored for any task, data set, and target inference hardware.

Deci’s AutoNAC engine democratizes NAS technology, something that until very recently was confined to academia or industry giants like Google due to its high cost.

Deci recently announced the launch of version 2.0 of its platform, which helps enterprises build, optimize, 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.

Deci collaborates with various hardware manufacturers, Computer OEMs and other ML ecosystem leaders, and is an official partner of Intel, Amazon Web Services (AWS), Hewlett Packard Enterprise (HPE), and NVIDIA among others.

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