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Tenyks, a University of Cambridge spin-out focused on helping machine learning engineers build better, safer artificial intelligence (AI), has raised a $3.4 million seed round. Tenyks’ platform helps developers understand what’s wrong with their algorithms, resolve issues, remove bias, boost model performance, and enhance data quality.
Co-founded by Botty Dimanov, Dmitry Kazhdan, and Maleakhi Wijaya, Tenyks has developed technology that provides insights for computer vision applications at an unprecedented granularity. Botty came up with a patent-pending invention that laid the foundations for Tenyks’ technology while working on his PhD. Dmitry and Maleakhi then spent two and a half years fleshing out the practical implications of the research as part of their PhD and Masters work and establishing the engineering scaffolding that could produce a reliable product.
Having gone through Y Combinator’s summer 2021 programme, Tenyks has come out of stealth and is working with five pilot users. Insights from Tenyks help engineers accelerate their development lifecycle, so they spend less time onboarding new users, reducing customer acquisition costs, and boosting the accuracy of AI.
“In one case, a machine learning engineer used Tenyks to identify the root causes of 80% of their algorithm’s failures. These findings helped them deliver higher quality results to their customers because of the significantly improved system performance. Moreover, future new deployments can be onboarded in half the time because the engineers can now focus their efforts on alleviating the key bottlenecks,” says Tenyks’ CEO, Botty.
Becoming the best part of a machine learning engineer’s day
The new funding will be used to double the startup’s software engineering team, bringing the company’s headcount to 12.
Tenyks aims to turn the most boring part of a machine learning engineer’s job—manually sifting through data to improve the success rate of their AI— into the pinnacle of their day. “Engineers get frustrated wandering in the dark, trying to figure out if the change they made will improve performance, and not having the insights needed to know what to do next. Tenyks removes this stress, making the process a breeze,” says Botty.
The round was co-led by Speedinvest and firstminute capital, with participation from LAUNCHub Ventures, Y Combinator, Cambridge Enterprise, Creator Fund, 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 $500 million as a former President of Product Groups at Arm, and John Taysom, who led the first investment in Yahoo in 1995.
Tenyks 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.” says Tenyks’ CTO, Dmitry.
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