Founder’s story: Darko Matovski & Maksim Sipos – causaLens

April 17, 2020

Can you tell us more about you and your background?

Maksim Sipos – founder, CTO: My academic background is in theoretical physics and statistical mechanics, it’s a field that tries to explain how systems composed of many different tiny parts behave at an aggregated level. I did my PhD in the US. A lot of physicists leave academia to go and work in finance, in hedge funds for instance. I worked in finance for a couple of years in a hedge fund that was using systematic strategies to trade in the market, it used science to trade financial instruments. Following on from that, I worked for another couple of years as a data scientist consultant at a number of companies, including some cool start-ups in London and Berlin. I also worked as an employee CTO in another start-up where I got my first experience managing tech teams, and then I met my co-founder, Darko. 

Darko Matovski – founder, CEO: I did my PhD in the area of computer vision, now everybody calls it AI, on a project analysing someone’s gait, the way they walk, to recognise them. As Shakespeare said, “Tis Cinna. I do know him by his gait“. I went on to commercialise my research at the National Physical Laboratory – where Alan Turing worked. After that, I too worked for hedge funds because I was reassured it was the best way to conduct really cool research in fast paced environment, outside of academia, which I later found not quite the case. Regardless, I was very fortunate to have worked for one of the best hedge funds on the planet – Man Group. I also did an MBA. 

So how did you both decide to set up CausaLens? 

Darko: We were in a Turkish restaurant and started agreeing with the famous saying that correlation doesn’t imply causation. We both strongly felt that that was something that hadn’t been properly solved. Soon we realised, given our similar backgrounds, that from the outside the world of finance appears incredibly sophisticated but from the inside, not so much. Which is incredibly significant considering finance is like the ultimate dynamic system where cause and effect matter a lot, so there was an opportunity here.

We’re both fascinated about understanding the world and understanding how it works. We felt that no single human, machine or team can do it with current technology because it’s way too complex and evolves so rapidly. We thought that there must be something that we could build, a fully automated technology that will understand cause and effect, that would be a good business and financial opportunity but more importantly, that it can help us understand the world. Over time, that’s where our vision was born, which is nicely explained in a line of code:vision = global_economy.predict().optimize() Our mission was to develop Causal AI, which we think is the only way for machines to understand complex systems, and that’s where our name CausaLens comes from.

“That’s where our vision was born, which is nicely explained in a line of code: vision = global_economy.predict().optimize()”

You’ve been working together for three years now, what’s next on the horizon? 

Our vision is infinite. We think that all the best companies have an infinite vision. If you think of examples of all the most successful companies, you will conclude that none of their visions have been fully realised and never will be. We found something we don’t think anyone was even close to thinking about. We’re very excited about working hard on that in the long term. In the shorter term we are very mission driven, and our mission is to develop Causal AI. On the research side, most of our resources are going to inventing a new theory of how machine learning works. And inventing the engineering to support that theory. On the product side, it’s about translating some of this research into products that we can scale for financial services, and also beyond that. That’s the way to realise our vision of optimising the global economy. Our vision is always there, developing Causal AI is a huge undertaking, rewriting the way that machine learning works. Current machine learning technologies are great at perfect learning past patterns. They don’t tell you anything about the future, and that’s what we are passionate about. Our research is already paying off, our product is infused with causality, which means that for the first time we can solve some of the problems that were never solved before.

“We found something we don’t think anyone was even close to thinking about.”

What’s your approach to hiring and how have you been successful so far? 

Darko: We are currently receiving 100 CV’s daily, equating to 25,000 CV’s a year. And that’s all competing for 30 positions in 2020. So needless to say, the acceptance rates and bar we have set for ourselves is extremely high. To be able to do that efficiently, we had to invent a new protocol as we cannot rely on traditional approaches. What has worked for us is engaging the entire company in the recruitment process and automating all things that can be automated along the way. How we run testing, how we store information, how we move people in the pipeline, how we test the culture fit. The part that cannot be automated is very human, like inspiring people to join you, understanding whether they have the same values as the company you would like to build, understanding whether their vision of themselves is in line with the vision of the company. 

“We want to change the world, and it would be very hard to do that if we have people that look at what’s going to happen next week.”

What sort of culture do you aim to cultivate at CausaLens? 

Maksim: we have got three values that we stand for. We try to keep it simple, we don’t want to be a company with too many values because we want to make them really good. The first one is a culture of kindness and inspiration. We want to ensure we are constantly kind and friendly, with a feeling of inspiration radiating towards each other. Secondly, we need to have people that are trustworthy, who have a sense of ownership and accountability for what they are working on. We need to rely on people, if there’s a problem, we know that they are going to take care of it. The third one is to thrive through adversity. This is a challenging technical problem, right? We need people that, when facing a setback can keep pushing, keep working on it, even when facing difficulty.

“We want to ensure we are constantly kind and friendly, with a feeling of inspiration radiating towards each other.”

How do you check the culture fit? 

We have done a lot of research on that, we’ve looked at how the best people in this field do. The drive and resilience came from a study that shows that grit is a key determinant to success in life, it’s the number one driver. It wasn’t background or education, it was just tenacity, how hard you’re working. We also observe a lot and talk to people a lot during the interviews.

“The drive and resilience came from a study that shows that grit is a key determinant to success in life, it’s the number one driver. It wasn’t background or education, it was just tenacity, how hard you’re working.”

Do you have any advice on what a board should look like and how you should run a board meeting?

It’s very important that everybody in that room has a skin in the game and has the ability to contribute in a given way, that is uncorrelated to the other members of the board in terms of experience and knowledge. We like to run our meetings and be very hands on. First, we have a strategy section at the beginning, where we talk about the strategic division of the company from multiple angles: hiring, product, research, customers, and so on. And then we have the second part where we dive into the details. And that’s really great because it allows us to get the most important things sorted first.

How did you come to choose IQ Capital?

Darko: We saw more than 50 VCs in our search for an ideal partner. For us the priority was having a partner that understands what we’re doing. And it was surprisingly hard to find people that even understood what we were trying to build. Just explaining what causality is, it was a struggle! With IQ Capital, we didn’t need to explain it, it was obvious from our name what we were about. It didn’t take long for us to feel comfortable and be assured that the feedback we’d get, would come from people that understand what our core mission and vision is. We wanted to avoid being in a boardroom where we’d be spending the majority of the time explaining what to us is pretty simple. We need people who know what to do with it, and can then advise us on a strategic, business level, what is the best way to position a company like ours. 

“It was surprisingly hard to find people that understood what we were trying to build. […] With IQ Capital, we didn’t need to explain it, it was obvious from our name what we were about. It didn’t take long for us to feel comfortable and be assured that the feedback we’d get, would come from people that understand what our core mission and vision is.”

Who inspires you in the scientific community?

Darko: Alan Turing, mainly because he was able to conceptualise AI during the Second World War. He was so ahead of his time.

Maksim: Mine is a science fiction author called Issac Asimov. One on one of his books is called “Foundation”. It talks about the far future that we’re building where mathematical equations can predict what’s going to happen. It was a big inspiration for me, I even mentioned it in my PhD thesis. 

How do you keep learning, how do you stay on top of things? 

Darko: It feels as though our job changes every three months, so we have to keep learning, it’s not a choice. We have a philosophy that we do not hire for a job before we have done it. Right now, we are working on how to do customer success for example, so we are hiring for that role, but we are also doing it. That way, when new people come in, we already are aware of the challenges and have already established the baseline of that job, the KPI design and everything else going with it. All this requires a lot of learning on the spot.

How do you switch-off and relax?

Darko: I thought that my PhD would be the most overconsuming experience, now in comparison it feels like it was a piece of cake! I’m into beach volleyball, I started playing when we started CausaLens and I’m now intensifying that. 

Maksim: I’m still trying to figure that out. I like nature so I enjoy going out somewhere where there are no computers, just greenery, where I can hike. I think I always carry a lot of my job with me though.