Deci, a Tel Aviv, Israel-based company developing a platform to optimize machine learning models, raised $21 million in a Series A.
The round was led by Insight Partners, with participation from Square Peg, Emerge, Jibe Ventures, Samsung Next, Vintage Investment Partners, and Fort Ross Ventures.
The investment which comes a year after Deci’s $9.1 million seed round, brings the company’s total capital raised to $30.1 million and will be used to support growth by expanding sales, marketing, and service operations, according to CEO Yonatan Geifman.
Company: Deci.AI Inc.
Round: Series A
Funding Month: October 2021
Lead Investors: Insight Partners
Additional Investors: Square Peg, Emerge, Jibe Ventures, Samsung Next, Vintage Investment Partners, and Fort Ross Ventures
Company Website: https://deci.ai/
Software Category: Deep Learning development platform
About the Company: Deci was cofounded in 2019 by Geifman, Ran El-Yaniv, and entrepreneur Jonathan Elial. Deci enables deep learning to live up to its true potential by using AI to build better AI. With the company’s end-to-end deep learning acceleration platform, AI developers can build, optimize, and deploy faster and more accurate models for any environment, including cloud, edge, or mobile. The platform is powered by Deci’s Automated Neural Architecture Construction (AutoNAC) technology, an algorithmic optimization engine that squeezes maximum utilization out of any hardware. The AutoNAC engine contains a Neural Architecture Search (NAS) component that redesigns a given trained model’s architecture to optimally improve its inference performance (throughput, latency, memory, etc.) for specific target hardware while preserving its baseline accuracy. Deci achieved a record-breaking 11.8x accelerated inference speedup on Intel CPUs at MLPerf Industry Benchmark and has been named to the CBInsights top 100 AI companies. Led by a team of world-class deep learning experts, Deci lets AI developers focus on what they do best - creating innovative AI-based solutions for our world’s most complex problems.