KSITEST: A startup that understood what the market needs

Interview with Daria Yakovishina, General Director of Xitest:

What is Ksitest? Tell us about your activities

We are engaged in genomic selection of animals, and today our company is the industry leader in Russia and the CIS. Our offer consists of two parts: the platform itself - the interface for working with genomic estimates of animals and, actually, the module for calculating genomic estimates and processing genetic data. 

Roughly speaking, we take the animal's DNA data and a common database that has information about the pedigree and many other indicators: how the ancestors behaved, how they gave milk, fat and protein, how long they lived, and so on. We put all this data into a predictive model and can make a prediction: whether the animal will be profitable. It is also possible to say in advance whether a cow, for example, will give more or less milk, whether it will live longer, and so on.

You make such an assessment not at the stage when a farmer buys an animal, but when he already has a herd, let's say. What is the usefulness of such a forecast in this case?

As a rule, animals are bought once or maybe several times over many years. And then at any enterprise - big or small - there is a certain process of animal selection, breeding. It's always been there, even thousands of years ago. What did farmers used to do? They would take one big animal, another big animal, and say, "If we cross them together, the next generation will probably be big too."

But there are some traits that are quite difficult to predict. Besides, the next generation of animals is influenced not only by genetics, but also by some environmental conditions. For example, you can say that an animal grew big not because it has a high genetic potential, but because it was fed better or walked a lot in sunny weather.

In the past, such things were determined "by eye" - you took a big bull and hoped that his children and grandchildren would be the same. But this was an inaccurate prediction. Now we can take into account all the data from several generations back and give recommendations on breeding.

How did you come up with this? Why did you choose this line of business?

Actually, genomic selection has been around for the last 15 years, but it is still quite an innovative thing. 

In Russia, they started thinking about introducing genomic selection, I think, about 7 years ago. We started working in this direction in 2019 together with my co-founder Yura Pekov. 

We have both been in biotech for quite some time. I have a PhD in bioinformatics, which I obtained at Ecole Polytechnique (Paris), where I worked on major rearrangements in the genome related to oncology. Yura has a master's degree in biotechnology from Moscow State University. But working in science, we realised that often the results from implementing your own research can be seen literally decades later, so we wanted to innovate where there was leverage and the opportunity to benefit sooner rather than later.

When we started the business, we didn't really know what direction we wanted to go in yet. We started with outsourcing for different areas. We had a table with all the areas where biotech could be applied: pharma, agro, food industry, and so on.

We started sending letters and that's how we got our first orders. At first it was mainly orders from science, but little by little the real sector started to appear. That is, we followed the bootstrapping model, we did not attract investment, we did not build our own laboratories. We even left our jobs not immediately, but only when we were able to pay our salaries from business. We had a goal, but there was no way, let's say, to work for several years without a salary, so we decided that if we couldn't find anyone who could pay for it, we wouldn't do anything. 

 

I think this is not a bad way to go. During the outsourcing period, we were able to understand what the market required, and since we did not attract investment and did everything on our own money, we had to make sure that the market really needed the product, rather than inventing a need. At some point we received an order from Miratorg. They said they wanted to introduce genomic selection of animals.

At that time, I think we had been working together for about a year, and we had 3-4 people in the company. And we thought: if they came to such a young company with such a request, there is no one else on the market at all. And indeed, this turned out to be the case.

"Miratorg eventually decided to do everything inhouse, but by that time we had already understood the market's need and made an MVP - a minimum viable product. And with this MVP, we signed a three-year contract with one of the biggest players in the market. The total amount, I think, was about 5-6 million roubles a year. It was a great deal for us. We took that money and started to finalise the product.



This, by the way, is very different from the stories I have heard from other portfolio companies. Usually they are stories about founders starting in a garage and spending years testing their product.

We were just trying to avoid that. And that's why we didn't take investments, because we had no experience. It seemed to me that taking money was too big a commitment for someone with no experience, and for a project with a raw idea. I didn't want to learn for other people's money. So we worked for a long time without raising capital - until about 2022. 

We still don't have our own laboratory, we send all the samples to other centres. Our product is primarily an IT platform and R&D module for calculating estimates. We have made models that work with the data and give a prediction for the animal.



What challenges did you face at the start?

Probably the biggest challenge from the beginning was that we didn't know this market. I have to say that when we started working, we literally didn't see these animals, we didn't see cows. We didn't understand how this sector worked, how farmers worked, how their processes worked, what the complexities were for our clients.

We knew how to do the mathematical model, but we didn't understand what happens afterwards. This was probably the biggest difficulty, because farmers are people from a completely different world, with other tasks, questions, problems.

 

It took us a long time to learn to speak the same language with them, to implement our product in such a way that it would be convenient to use it. This process is still ongoing. We have been working for five years now, and all these years we have mainly spent on figuring out how to explain to people what we have done.

How do you evaluate the results, do you get feedback from farmers?

It's quite a complicated story. You have to wait a few years to see the real returns, because the next generation of cows has to be born and start producing milk. But we have a big flagship project in Udmurtia. We launched it in 2020. And by 2023-2024 it became known that there are successes.

For example, the whole region milked a million tonnes of milk and rose from fourth place to third place in the country. Previously, the increase in milk productivity per year was 2-3%, after we introduced genomic evaluation, this figure rose to 7%. This is a huge success. At the same time, investments in the industry were small - about 50-60 million roubles over three and a half years. This is very little for a dairy region of this scale. Recently, it has become clear that genomic evaluation will become a standard throughout Russia. And the main thing for us is to take over the market as soon as possible.

 

Do you currently have any analogues? Do you see any competitors for you?

There are companies that deal with genomic evaluation of animals. But we probably have the most advanced product, simply because of the number of evaluations, i.e. the factors we can evaluate: milk productivity, fertility, survival rate, exterior traits. Now we have over 45 evaluations, our closest competitors have 6-9. We have our own product, and probably the most experience in implementation. There are other teams, but they tend to have a slightly different focus. Someone works more with seed - they sell it and make it their main business, and assessments are an add-on. Some are more involved in consulting - they come to the regions, discuss with farmers what is needed, do genomic evaluation and somehow share it with them further. But it is an R&D and IT product like ours that is unique on the market.

So, conventionally, you can even make a more beautiful cow? 

Theoretically, yes. We have about 20 evaluations on external indicators: leg position, udder size, muscularity, and so on. But these indicators are needed more for health work, there is usually no practical sense in making a "very beautiful cow".

 

How did your co-operation with KAMA FLOW begin?

Kirill Tishin and I studied together on the same course, in the same year. I think that he occasionally saw some announcements on my social networks, where I wrote about our project. For example, an article about us in Izvestia or Vedomosti. In 2021, he wrote to me that if you suddenly needed investment or help, you could contact me.

In 2022, when the famous events began, we were supposed to have a big round with another investor. And it fell through.

The market was very volatile then and the whole sector froze. We decided to turn to KAMA FLOW for investment, and we did everything quite quickly on Zoom, literally in a month and a half. The guys are great in this respect: they make decisions quickly, immerse themselves in the idea of the business, without the classic bureaucracy. After that, we had two more rounds with them - in 2023 and 2024.

KAMA FLOW helped with attracting the next rounds as well. Anyone who runs a business knows that this is the number one issue in terms of importance. Attracting a round is a long process that takes up a huge amount of the team's time. They took it upon themselves: negotiating, making arrangements. That's very valuable. In addition, they help with negotiations with major players in the industry, for example, if they are HR contacts.