Cambridge startup ramps up $3.4 million to show how AI can make human connections deeper –

University of Cambridge spin-out Tenyks has raised a $3.4 million seed investment to help machine learning engineers build better, safer AI. The round was co-led by Speedinvest and firstminute capital, with participation from  LAUNCHub Ventures, Y Combinator, the University of Cambridge, Creators Funds, Remus Capital, CSVE Ventures, RKKVC, Black Mountain Ventures, and a dozen angels, including the co-founders of Privitar (market leader in data privacy and data governance), Pete Hutton who developed products worth over $500m as a former President of Product Groups at Arm, and John Taysom who led the first investment in Yahoo in 1995.

Founded by Botty Dimanov, Dmitry Kazhdan, and Maleakhi Wijaya, the startup’s helps machine learning engineers working with computer vision data build more reliable software, faster. Like a ‘doctor for AI’, it helps developers understand what is wrong with their algorithms, resolve issues, remove bias, boost model performance, and enhance data quality.

Having gone through Y Combinator’s summer 2021 programme, it has now come out of stealth and is working with five pilot users. For example, insights from the platform help engineers spend less time onboarding new users, reducing customer acquisition costs and boosting the accuracy of AI.

The platform is attempting to invent the way humanity interacts with AI. Botty, CEO, Tenyks said: “Every time technology pushes the boundaries of the impossible, a category-defining product emerges to open the door for widespread adoption. Computers had graphical user interfaces and the internet had search engines. AI will have collaborative platforms that allow us to program and interact with data and unlock the full potential of artificial intelligence.”

The new funding will be used to double the startup’s software engineering team, bringing the company’s headcount to 12. “We are building a culture which makes it contagious to pour your heart and soul into building the product that can become the data explorer for machine learning,” Maleakhi, Founding Engineer, Tenyks added.

Going forward, the platform will develop an ecosystem of products designed to make the job of a machine learning engineer easier, while reducing the learning curve necessary for developing, understanding, monitoring, and auditing AI. “Gradually, in the same way coding is now a required subject in schools, AI programming will be a commonplace skill empowered by Tenyks products.” Dmitry, CTO, Tenyks said.

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