aiOla's Alon Peleg

Appointment
aiOla appoints Alon Peleg as Chief Operating Officer

“Alon's addition couldn’t have been more well-timed, and I’m delighted to have him by my side in leading aiOla’s rapid expansion,” said Amir Haramaty, co-founder and CEO.  

Speech recognition technology company aiOla has announced it has appointed Alon Peleg as COO. He joins the company to help streamline operational efficiencies while accelerating aiOla’s global expansion.
"I'm thrilled to be joining the exceptional team at aiOla,” said Peleg. “aiOla’s solutions are significantly improving inspection processes across industries enabling businesses to automate, and enhance critical operations effectively. I'm enthusiastic about working alongside aiOla's world-class team of research scientists and AI experts, optimizing and scaling operations around product development and go-to-market to drive aiOla's expansion. Moreover, I’m eager to empower more enterprises to leverage aiOla's state-of-the-art AI solutions.”
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aiOla alon
aiOla alon
aiOla's Alon Peleg
(Photo: aiOla )
Peleg joins aiOla with more than 20 years of experience, notably as General Manager at Wix and CISCO and Division Manager at Intel. He has helped with creating and executing strategic visions, spearheading product roadmaps, and driving growth for a range of companies.
“Alon's addition couldn’t have been more well-timed, and I’m delighted to have him by my side in leading aiOla’s rapid expansion,” added Amir Haramaty, co-founder and CEO of aiOla. “With his rich technical and managerial positions at leading tech companies, Alon brings a unique blend of product knowledge, R&D strategy, leadership, and customer-centric innovation that will prove invaluable as we continue to deliver immense value to enterprises across the board.”
aiOla uses patented technology to understand more than 100 languages and discern jargon, abbreviations, and acronyms. Its technology converts manual processes in critical industries into data-driven, paperless, AI-powered workflows through speech recognition with low error rates in noisy environments.