deci raises $9.1m to optimize ai models with ai

Deci, a startup headquartered in Tel Aviv and focused on developing a platform that leverages artificial intelligence to refine and prepare AI models for practical application, today announced the successful completion of a $9.1 million seed funding round. The investment was spearheaded by Emerge and Square Peg.
The core concept behind Deci is to streamline and accelerate the process of deploying AI-driven tasks for businesses – and to enhance the precision and efficiency of those deployed models. To achieve this, the company has created a comprehensive solution that allows engineers to import their existing, pre-trained models. Deci then handles the management, evaluation, and optimization of these models prior to packaging them for implementation. Through its runtime container or Edge SDK, Deci’s users can subsequently deploy these models across a wide range of contemporary platforms and cloud environments.
Deci’s insights display consolidates all indicators of a deep learning model’s anticipated behavior during operation, culminating in the Deci Score – a unified metric representing the model’s overall effectiveness. Image Credits: DeciThe company’s founders include Yonatan Geifman, a deep learning scientist; Jonathan Elial, a technology entrepreneur; and Ran El-Yaniv, a professor of computer science and machine learning expert from the Technion – Israel Institute of Technology.
“Deci is spearheading a fundamental change in the field of AI, providing data scientists and deep learning engineers with the necessary tools to develop and implement impactful and robust solutions,” states Yonatan Geifman, CEO and co-founder of Deci. “The increasing intricacy and variety of neural network models present significant challenges for companies aiming to achieve peak performance. We recognized that utilizing AI itself is the most effective approach to overcome this obstacle. Through the use of AI, Deci aims to empower every AI professional to address the world’s most challenging problems.”
Deci’s lab interface allows users to oversee the complete lifecycle of their deep learning models, improve inference speed, and prepare models for deployment. Image Credits: DeciThe company asserts that, while maintaining equivalent accuracy, Deci-optimized models can operate five to ten times faster than previously possible on the same hardware. It supports both CPUs and GPUs for its inference workloads and currently collaborates with clients in sectors such as autonomous driving, manufacturing, communications, and healthcare, among others.
“Deci’s capacity to automatically generate high-performing deep learning solutions represents a transformative advancement in artificial intelligence and opens up new possibilities for numerous businesses across diverse industries,” commented Liad Rubin, partner at Emerge. “We are delighted to support such talented founders and participate in Deci’s growth from the outset.”