Deci.AI Ltd. is getting a $21 million cash infusion via an early-stage round of funding aimed at furthering its mission of helping companies build, optimize and deploy artificial intelligence-powered applications.

Today’s Series A round was led by Insight Partners and saw the participation of existing investors Square Peg, Emerge and Jibe Ventures, plus new investors Samsung Next, Vintage Investment Partners, and Fort Ross Ventures. The round brings Deci’s total amount raised to $30.1 million.

Deci has created a development platform for deep learning aimed at making it easy for AI developers to build, optimize and then deploy their models quickly, in the cloud, at the edge or on mobile devices. The key benefit of Deci’s platform, according to the company, is it helps to shorten development lifecycles and reduce the cost of building new models while still ensuring high performance and accuracy.

Deci says that’s needed because long development times, along with high costs, are major roadblocks preventing AI being adopted at many smaller organizations.

Deci co-founder and Chief Executive Yonatan Geifman told SiliconANGLE that deep learning development is a complex lifecycle with multiple stages that demand a range of skills. As a result, there are typically many different people involved in the process.

“This leads to a disconnect between the way models are designed and evaluated during the development stage and how they should perform in production,” Geifman said. “These major gaps translate into endless back and forth iterations and manual tweaks, which tend to result in poor performance and project failures.”

Deci overcomes these challenges through its Automated Neural Architecture Construction technology. AutoNAC, as it’s called, is an algorithmic optimization engine that automatically creates deep learning models for any task, based on the data it’s fed and the target inference hardware. So all developers have to do is define the task or problem they want to solve, provide some data and specify the hardware that model will run on, and Deci does the rest.

Geifman said AutoNAC creates the best possible neural network for each specific set of production requirements.

“Models that were generated by Deci’s solution have been proven to deliver superior accuracy and performance,” he claimed. “Leveraging the same process, Deci optimizes existing models as well. Its platform includes a complementary set of tools that help to streamline additional stages in the development lifecycle.”

Deci’s other co-founder, Chief Scientist Prof. Ran El-Yaniv, said AutoNAC can be used to create high-performing classification and detection models, among others.

“Our technology is used for any deep learning task, be it vision or natural language processing,” he said. “Due to the fierce deep learning race to produce more powerful neural networks, AutoNAC is continuously improved so that Deci’s customers will always receive the strongest models.”

Deci cited its work with Intel Corp. as proof of its capabilities. The company recently collaborated with the chipmaker at MLPerf, an organization that has created a series of performance benchmarks for AI models. Deci said AutoNAC was able to accelerate the inference speed of the popular ResNet-50 neural network on several different Intel-made central processing units. In the wake of that showcase, Deci announced it’s working with Intel on an ongoing basis to optimize deep learning inference for all of the company’s processors going forward.

Deci’s other co-founder, Chief Executive Yonatan Geifman, said today’s funding round is a vote of confidence in his company’s work.

“Amidst an increase in the adoption of deep learning models, shortening time to market and increasing the success rate in production is becoming critical as more and more enterprises look to commercialize their deep learning-based solutions,” he said.

The next step for Deci is to accelerate its commercial growth, which it plans to do by expanding its global sales, marketing and customer success teams.

Images: Deci