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Combining natural language and artificial intelligence solutions to help traditional manufacturing industries

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2023-05-02 10:13:061641browse

Israeli startup aiOla announced that it has received $25 million in funding. The round was led by New Era and also included Hamilton Lane and other investors. The Israeli startup develops advanced voice and image recognition technology combined with advanced artificial intelligence models to digitize, automate and simplify inspection processes in traditional industries. The company's goal is to significantly reduce customers' operating costs, increase production time, automate trend reporting, and minimize downtime.

Combining natural language and artificial intelligence solutions to help traditional manufacturing industries

To date, aiOla has raised $33 million in funding and employs 55 people, mostly in Herzliya, Israel. The company’s founders are CEO Amir Haramaty and Guy Ernst, former Google CTO and Amazon Director of Artificial Intelligence Architecture.

"The artificial intelligence revolution has not yet succeeded because artificial intelligence is currently mainly used by data scientists. We can make artificial intelligence available to everyone." Amir Haramaty said. "aiOla's proprietary natural language interface patented technology is ideally suited to the current 'gold rush' of artificial intelligence. Our technology spans any language or terminology for any process, delivering immediate and lasting impact across a variety of industries and verticals."

Haramaty noted that he was very pleased with the interest in the company from investors such as New Era and Hamilton Lane, as raising capital was very difficult at the time. He explained that the company is focused on applying its solutions to "must-have" industries, such as the food and medical industries.

Gideon Argov, Managing Partner of New Era Capital, said: "We are excited to partner with Amir and the entire aiOla team. The company's breakthrough technology will help enterprise customers save valuable time and improve Accuracy of critical operational recommendations and reporting, and breaking down language barriers between geographies and business units.”

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