Tenyks lands $3.4m for human-AI interaction to fend off the ‘terminator’
Tenyks, a University of Cambridge spin-out focused on helping machine learning engineers build better, safer AI, has raised an impressive $3.4 million seed round.
The startup’s platform helps machine learning engineers working with computer vision data build more reliable software, faster. Like a ‘doctor for AI’, it helps developers understand what's wrong with their algorithms, resolve issues, remove bias, boost model performance and enhance data quality.
Tenyks was co-founded by Botty Dimanov, Dmitry Kazhdan, and Maleakhi Wijaya. They’ve 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 2.5 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 now come out of stealth and is working with five pilot users. For example, 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.
Dimanov says: “In one case, a machine learning engineer used Tenyks to identify the root causes of 80 per cent 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.”
The new funding will be used to double the startup’s software engineering team, bringing the company’s headcount to 12.
Maleakhi Wijaya said: “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.
“But what is different about Tenyks is that we are not just about achieving. We are about happily achieving. We find joy in everything we do, including and especially when it is most challenging, because that’s when we grow the most. We even measure how many times we laughed during the week.”
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.
Dimanov added: “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.”
The seed round was co-led by Speedinvest and firstminute capital, with participation from LaunchHub; 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.
• PHOTOGRAPH: From left – Botty Dimanov, Dmitry Kazhdan and Maleakhi Wijaya
