Arato Raises $10 Mn in Seed Round led by TLV Partners

The funding round was led by TLV Partners, with additional investment from Jibe Ventures, Raghu Raghuram (partner at Andreessen Horowitz and former CEO of VMware), and Marianna Tessel (former CTO of Intuit).

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Arato has developed a platform that helps companies test their AI systems. It studies how an AI system works and creates thousands of real-life scenarios that imitate how people would use it.

The platform tests the AI through its existing interface, including text, voice, images, and business data. It does not require access to the system's code or complicated setup.

“For many years, the software industry focused on whether a system works or not. In the AI era, the more important question is whether it is ready for business use in the real world,” said Shahar Erez, CEO and Co-Founder of Arato. “There is still a long way to go before AI-based systems meet customer expectations, especially when we are not talking about general-purpose tools such as ChatGPT, but about business-critical applications. Every organization adopting AI knows the system will not meet expectations 100% of the time. The question is how often it will fail, in which situations, and what the potential damage could be to users and to the business. Many organizations are launching AI today simply so they can say they have AI, but that will not hold for long. The next stage is bringing these systems to a level of maturity where they solve a business problem and create value. Arato makes it possible to measure that systematically before customers discover the problems themselves.”

Founded in 2024 by Shahar Erez, Hilik Paz, and Tal Salmona, Arato has built a platform that helps companies test how people may interact with their AI applications before they go live. It allows developers to create thousands of test scenarios using text, images, voice, and business data.

The platform then analyzes the results to find common problems, identify possible risks, and show where the AI system can be improved before it is launched.