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Excellent playground for AI AI is not just hype. It is real. Almost every company in every industry needs to think about it for future success. And the Baltic States have much to offer.
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Photo: AdobeStock
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by ANDRE JS MĒTER S & ALE X ANDER WEL SCHER
Bringing AI to every industry AI is nothing new and has been around since the 1960s, claims Aigars Jaundālders, CDO of WeAreDots. “I’m an applied maths guy and come from an operations research background. What I have been doing is optimizing complex models for the past 20 years or so”, says Peeter Meos, Data Science Technical Lead at Proekspert. He adds that the only thing is that back then they called it mathematical optimization and operations research, not AI. Just the same thing with a different name. “Nowadays, everything is in data science or AI. But the stuff with these name tags has been around for decades”. We introduce five modern time AI companies from Baltics.
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why is everybody now talking about AI? The difference in the last decade or so was that specific technologies met an abundance of data. And when you pair these together, you get the wonderful things we see already today everywhere, explains Jaundālders. “We feed the machine huge amounts of data. For example, we give a machine thousands of images of conventional cars and thousands of images of taxis or municipal buses”. And the machine really learns how to tell whether it’s a taxI or a conventional car. And it learns both how to tell and which features to consider. It’s like teaching a machine to make these decisions. And this is the fundamental difference. “You have to live with this understanding that, most of the
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time, you can’t even explain exactly why AI made such a decision”, the WeAreDots expert recognizes. Artificial intelligence actually became possible with the development of superpowerful computers, which are accessible to everyone. The second thing is the data storage: we can store nearly an infinite amount of data and the search algorithms. Jaundālders also points out that 5G is not about faster YouTube. For transportation, for example, it opens some very interesting new use cases which were not previously technologically possible. A real technological disruption is happening in the market and some things can be done better now than ever before, emphasizes co-founder and CEO of Exacaster Šarūnas
Chomentauskas. “We started before AI was cool and hyped. So when the AI hype came, we had enough experience and were able to deliver. All of a sudden, we got this big hurricane blowing into our backs”. Today, Exacaster employs 80 people and was named in the Top 50 fastestgrowing companies in Europe several times in a row. For them, it is just the beginning. “Now we are once more in discovery mode of how to make this a more global business. Today, about half of our revenue is from North and South America”, says Chomentauskas. Since AI has become feasible for business, it has also already seen different applications across various industries in the Baltic states. In Estonia, Milrem Robotics, Starship Technologies and Cleveron have used
A real technological disruption is happening in the market and some things can be done better now than ever before
Photo: shutterstock
the technology to develop unmanned ground vehicles that can work autonomously and carry out certain tasks. In the telecommunications sector, Elisa Estonia uses AI to create chatbots that improve customer service and the company is working on personal identification based on facial recognition. For this purpose, the telecom provider partnered with the AI consultancy MindTitan that specializes in developing custom AI and machine-learning solutions. The Tallinn-based firm has created market use cases for
AI in the pharmaceuticals and healthcare industry, in aviation, travel and the finance sector. In a similar way, Latvia’s IT companies WeAreDots and KleinTech have developed industryspecific solutions such as a poultry management system and selflearning automated inspection solutions for the transport and security industry. Telecom operators have also embraced AI: Lattelecom has automated its customer support with a chatbot, while Tele2 has
launched one to look for new employees. The latest development in this area is an AI news anchor that was presented by the internet portal DelfI at the end of February at the TechChill conference in Riga. In turn, the Lithuanian market research firm Kantar TNS uses AI to monitor and convert audio and video recording to text. They developed many of the multilingual virtual assistants and the automatic text or speech recognition technology in use by the language tech company Tilde that also offers AI-powered machine translations. One of the pioneers using neural networks for processing language text and speech, Tilde is working to implement further AI technologies
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This is one extreme and it is far from true: machines in general are not as good as people. And there’s another extreme saying that AI is useless because operations are too difficult. In reality, AI is a very efficient instrument. But you have to know where and how to apply it. “Therefore, when we talk with our customers we spend quite some time to understand their business and to build realistic expectations and scenarios on how to apply AI to meet their business needs, as well as improve efficiency, quality of customer service and speed of delivery”, says the CEO of Tilde.
AI will have a profound long-term impact in almost all the areas. To secure future success, it‘s very important to start using AI now to stay on top for various solutions in its home markets, which are among Europe’s most linguistically complex languages. “Baltic countries are an excellent playground to pilot new AI applications and test technologies”, says CEO Andrejs Vasiļjevs. This view is shared by the US firm Cujo AI, which develops solutions based on AI and machinelearning technologies for both telecom companies and home users. The company has chosen Lithuania as the location of its first office outside the home market and is developing, testing and improving in Vilnius and Kaunas.
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At the same time, Vasiļjevs warns that there is a lot of hype with AI and there are exaggerated expectations that AI can do everything and will be able to replace human workers.
That is why it will not be a fast process. “If you look at history, the impact of the internet took 20 years and it’s still going. It’s something like a hundred-year cycle. Everything will probably be understood as one big information revolution, including the internet, artificial intelligence, computing and so on”, says Chomentauskas.
Photo: shutterstock
AI is a transformative technology and it’s entering areas that previously were only occupied by humans. “What we are seeing is that AI will have a profound long-term impact in almost all the areas. To secure future success, it’s very important to start using AI now to stay on top”,
says Vasiļjevs. He believes that it in 5-10 years, many industries and businesses will not be able exist without AI if they want to remain competitive. “If a business wants to stay competitive in 10 years’ time, it has to deploy AI. And this applies to most sectors”, adds Kristjan Jansons, co-founder and CEO of MindTitan. He sees it as a mission to bring AI to every industry. “A few years ago, nobody was sure if the AI hype was real or not. Now, it’s definitely real.” It is essential to think about it now. If you don’t, your competitors in Finland, Germany or France will, adds Jaundālders. “It’s a necessity and it’s a reality. You don’t have to be Google to use these things”, Jaundālders noted.
To really use artificial intelligence, the process has to be digital – it’s connected, automated, has a feedback loop and can learn by itself. The reality is that a majority of businesses are still not there. If you take a few highly digital businesses, they are now using the best possible technologies. Co-founder and CEO of Exacaster Šarūnas Chomentauskas has observed that any company with a longer history than three years has lot of things that need to be fixed before artificial intelligence can truly have a big impact. “You must have data”, explains Jaundālders, pointing out that unless a company has data it cannot use AI. So before it starts going in a digital direction, a company has to have electronic records, such as data about customers or from digital sensors.
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- Proekspert -
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roekspert started from practical industrial application: we had a thermostat that always measured temperature a little bit wrong and it needed to be calibrated. The calibration was non-linear and not obvious. So instead of having a simple lookup table or something that that you need to do when you install a new thermostat, the guys built an AI model to take care of the calibration by itself. And that was the first AI project for Proekspert – eight years ago.
Photo: Diana Unt
Our focus is industry. We do industrial applications and embedded design like for frequency converters and also the user side of that. And
therefore our specialty in AI is also industry – the product that a particular industry is making and its production. Basically, our focus is on three things: production optimization with AI, predictive maintenance or smart maintenance solutions, and product digitization. If a company produces pumps, electrical motors or devices, we will help to make these devices “smart”. I don’t see many companies doing industrial solutions with AI. There are just a few in Europe. Estonia has been fairly well covered. Smaller companies, as most Estonian businesses are, do not get their return of investment on
– Peeter Meos Data Science Lead
AI. I don’t want to say their problems are simple, but their problems are not suited for heavyweight solutions. So we are targeting Germany and German SMEs. We don’t think we can offer anything to Siemens or Bosch. They are good enough on their own. But medium-sized companies are something that we are interested in. They are digitizing themselves for the foreseeable future, for the next 5-10 years. But they need some assistance there. AM
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- Tilde -
AI is a kind of umbrella term for a range of technologies that focus on human abilities and intelligent work. Language is
where humans are very strong and we use it for communication, for transferring information and for conceptualizing the world. We work to enable AI to understand and communicate in human language. In particular, we use deep machine learning technologies like deep neural networks. These are techniques that mimic the human brain with computing methods involving millions of cells. And these neural networks can be trained with human data to understand language and then translate speech for cognition. Like humans and the way a small child learns how to speak from examples by communicating with people around them, we train machines using examples of human language, translations and speech to understand our language. We do not limit our operations to the Baltics. Rather, we see ourselves as a European company and cooperate a lot with companies and research centres across Europe. One of our key cooperation partners is German Research Center for Artificial Intelligence (DFKI). AM
– Andrejs Vasiļejvs Chairman of the Board
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Photo: Kaspars Garda
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ilde is a leading language company in Europe. Our passion and mission is to enable users of various language communities to enjoy the same opportunities and possibilities using the latest technologies as the largest language communities. We work to promote language diversity and ensure security in the world of technology. We develop technologies like machine translation, speech technologies for text-to-speech and speech-to-text, artificial intelligence solutions for virtual assistants and smart chatbots, as well as other technologies that can understand and speak in various languages. We do significant work for the languages in Baltic countries: Latvian, Lithuanian and Estonian. And we believe that these languages are small in their number of speakers, but just as important for Europe and the whole world as other languages, and therefore deserve good technologies and technological support.
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- Exacaster -
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xacaster applies artificial intelligence to customer experience and customer value management. In the Baltics, we have two big, well known brands as clients – cell operator Tele2 Group and the retailer Rimi. We help these companies to be more competitive in the digital age. Maybe you can feel our work sometimes: every message you receive from Tele2 goes through our technology and all of the offers from Rimi become personalized through our platform.
Photo: Mindaugas Mikulenas
Ten years ago, we were working for a mobile company called Bite in Lithuania, which expanded into Latvia. We had to build a new company from scratch, go through all of the lessons learned, correct our mistakes and then finally we saw some success. All the while, there was one thing that we began to understand – you cannot really see your customers because there are too many of them. You can talk to one or two or three or ten, but you cannot talk to hundreds of thousands, so you have to look at data. And at that point, all we could do was to spend all our time looking at “Excels”.
One guy in the team quit his job to study mathematical statistics. Everybody said, “Well, you are stupid! You have a great career and you are going to university, dropping everything. It doesn’t make sense”. But it was actually a very good decision because at that time in 2010 there was a very good professor at the university. He saw this young student and recommended him to study algorithms that used machine learning, telling him that these algorithms would help solve problems that otherwise would be too time consuming or even impossible to solve. Several years later, I met him in the street and he said, “Oh I now know how to solve the problem that we had when looking through the Excels”. And I said, “Well let’s find out”. We went to a small cable company and said, “We think we can predict which customers will leave you. If you give us data for a trial, it will cost you nothing. It will be free of charge”. And they said “Ok”. We did the real test and our predictions were quite accurate. But we drew the conclusion from this experience that we had to work for large companies. AM
– Šarūnas Chomentauskas Chief Executive Officer & Co-founder
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he founders are a group of friends and the company came together in a hackathon. We went together to a hackathon where we built a facial recognition solution and an agent selection system. That was a project we worked on for a couple of months. During those months, we discovered that there are many businesses we could be useful to. So we started to build some custom stuff for businesses and went from there to build an entire suite of solutions. We take data from businesses, build the AI models and the outcome is either a prediction, some insight, or a recommendation on what is relevant in this case. Hopefully, the end goal for all concerned is profit – either a cost reduction,
a revenue increase or some new insights. In one sense, Mindtitan is an agency, and in another sense we call it a solution selling company. We have a set of core products, but customization is almost always needed since our work depends heavily on the data that businesses or institutions have. The core is the same, but we usually have to modify. Our main solutions deal with customer service and customer experience, pretty much the same for all industries, of course, with modifications. The other cases we have are more industry-specific. For example, if the client is in telco, then we need to analyze the network data. If it’s an energy company, we analyze the energy network data. If
it’s a pharmaceutical business, we have to analyze the production of medicine. And if it’s in the finance sector, we will look at fraud or anti-money laundering solutions. Our focus at the moment is still Europe, but we have done projects in the USA and Canada, and it’s very likely that we will also work in the Middle East and South East Asia. Of course, we also have Estonian customers but our focus is global. AM
from right to left
– Markus Lippus Co-founder, Data Science Lead – Kristjan Jansons Co-founder, CEO – Robert Roosalu Co-founder, Data Science Lead
- Mindtitan -
Photo: Diana Unt
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- WeAreDots -
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have a hundred employees and are a large or small company, depending how you look at it. We do custom development for customers who need something highly specific. We didn’t decide that we want to do AI. We decided that we want to work in transportation and then AI came as a natural fit because when we started on this specific product four to five years ago, it was actually the moment when AI really came into the mainstream. Today, our flagship product is a solution for traffic safety called FITS which is pretty much all about AI. Our customers are municipal organizations and governmental agencies of various sorts. They have different sensors and different things already deployed. But like in a zoo, there is a multitude of things out there, each signalling something and the data usually ends up being in millions of systems everywhere. Our core idea is that we provide a single central hub where all the data is ingested, processed, fused with AI and then, depending on the
customer, specific business processes are automated, including enforcement, issuing a ticket or maybe optimizing a traffic light signal plan to decrease travel time, and so on. FITS allows you to detect upcoming issues, pre-process speeding violations, enable rapid response, ensure statistical analysis and educate drivers about being safe on the road. Since its introduction in 2016, the number of traffic accidents has dropped by 47% and serious traffic accidents by 45%. Our main target market is the EU. In the transportation field, we are pioneering in Europe at the moment. There are not so many companies who are known for working with AI applications in the transportation field. People in Europe are still going around the country and plugging USB sticks into speed cameras to get data out of them or, in the best case, they drive to the pole and connect to the local Wi-Fi to download data. We basically automate all the things that previously took ages to complete. And this is specifically where AI comes into the frame. AM
– Aigars JaundÄ lders Member of the board, Chief Digital Officer
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