Tenyks, the Cambridge University spin-off startup, closed a $3.4M round for the development of its MLOps tools platform that helps machine learning engineers build better and safer AI. Tenyks is co-founded by the Bulgarian PhD student Botty Dimanov, and has recently graduated from Y Combinator.
The investment round was co-led by Speedinvest and firstminute capital, and was joined by LAUNCHub Ventures, Y Combinator, the University of Cambridge, Creators Funds, Remus Capital, CSVE Ventures, RKKVC, and Black Mountain Ventures. Around a dozen angel investors, including John Taysom who led the first investment in Yahoo in 1995, also participated in the round.
Founded by Botty Dimanov, Dmitry Kazhdan, and Maleakhi Wijaya, Tenyks is building an MLOps monitoring and validation platform that helps AI developers working with computer vision data to build more reliable software faster. The startup allows engineers to identify if there is something wrong with their algorithms, remove bias and resolve issues, as well as boost overall model performance, and enhance data quality.
“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,” Botty Dimanov, CEO of Tenyks, shares with The Recursive.
“The vision, the experience, and the culture of the team make investing in Tenyks a very easy and exciting decision. It is time to make the AI ‘black boxes’ a thing of the past, by providing transparency to their customers and their creators,” Stanislav Sirakov, General Partner at LAUNCHub Ventures, adds.
To better understand the solution of Tenyks and hear about the entrepreneurial journey of the team, The Recursive met with Botty Dimanov. Read further to find out more about their “doctor for AI” platform and YC experience.
When AI, academia, and entrepreneurship passion meet
The idea of Tenyks was born during the time when Botty Dimanov was working on his Ph.D. He came up with a patent-pending invention that laid the foundations for Tenyks’ technology.
“I wanted to be someone like Elon Musk, an entrepreneur who transforms whole industries with his products. But at the same time, I admired people like Thomas Edison, the inventor who sits in the basement, who creates a life-changing product and shapes generations to come. And my struggles came from the fact that I couldn’t choose one of the two paths. Instead, I just decided to do them both at the same time,” Botty Dimanov shares.
During his Ph.D. in AI at the University of Cambridge, he joined the Entrepreneurs First accelerator program. “It took me a long time until I came up with this idea. In the meantime, I was involved in developing a couple of smaller startups, including one audiobook startup which I eventually exited. In the meantime, I never stopped going to events, volunteering at startup clubs and conferences, and just keeping an open eye for an extraordinary person with whom I can start working on my next deep tech idea,” Botty says.
Eventually, he met Dmitry Kazhdan and Maleakhi Wijaya, who were doing their Masters and Ph.D. at the University of Cambridge, working on the practical implications of AI research.
Can we build safe AI? Defining how humanity interacts with AI
“AI development is changing from a model-centric approach to a data-centric approach. Based on many years of research at Cambridge University, Tenyks has developed a data-centric platform that can help machine learning engineers to have more granular insights on data, assessing the reliability across different relevant data sets and then finally improve the model and results,” Rick Hao, Partner at Speedinvest, highlights.
The goal of Tenyks is to eliminate the frustrating part of the job of ML engineers, namely the manual sifting through data to improve the success rate of their AI. Dimanov explains that engineers spend a lot of time trying to figure out if the change they made will improve the performance of the algorithms. And the fact that they don’t have any insights, prevents them from having a clear roadmap of what to do next. This is where MLOps tools come into play.
Tenyks develops an ecosystem of products designed to reduce the learning curve necessary for developing, understanding, monitoring, and auditing AI. Therefore, by helping ML engineers eliminates mistakes in the algorithm early on, Tenyks aims to ensure that the autonomous development of the algorithms happens safely, thus, protecting the world from the “AI terminator”.
Through YC and beyond
The co-founders got accepted into the Summer 2021 cohort of Y Combinator – the accelerator program which some may describe as the “Army for Founders”.
“First, one of the biggest value-added elements from participating in the program is the identity you gain. The YC aims to shape you as a “more formidable founder”. Another special element is the peer group of outstanding individuals that encourage you to give your best to first reach their level and then surpass them. In addition, hearing how graduate founders such as those of Airbnb or Stripe, talk honestly and openly about their mistakes makes you confident that you are on the right track,” highlights Dimanov.
Tenyks was previously backed with a $125K pre-seed funding from Y Combinator and supported with non-equity assistance from Creative Destruction Lab. After graduating from the YC’s summer 2021 program, the startup is now starting to gain momentum and is currently working with five pilot users.
With the latest funding, Tenyks aims to double its software engineering team, bringing the company’s headcount to 12. Currently, they are also hiring in Bulgaria.