We talked to Serguei Alechine of Ovotor on how they’re bridging the gap between data and decision makers.
First of all, how are you and your family doing in these COVID-19 times?
Serguei Alechine: We are doing quite fine, thank you. Some of our team members’ families are located in different regions or overseas. In the context of restricted international traffic, it became hard to physically visit the relatives as often as in the pre-pandemic times, but thanks to our habits in remote communications, which is a part of our DNA, we have coped with this situation well and are happy to see the progressive reopening of the borders.
Tell us about you, your career, how you founded Ovotor?
Serguei Alechine: The beginning of my path reflects the hybrid nature of the rest of it. During my Computer Science university years, I worked in a bank. My first position was already double-hatted: I was in charge of trading analytic support and developing decision-making software based on technical analysis methods and emerging Machine Learning techniques. Later I went through marketing and sales management roles across various industries and had the honor to work for global leaders such as L’Óreal, Legrand, Eberspaecher, and Bolloré.
I co-founded Ovotor in 2017 with my former colleagues when we realized the potential of rising technologies like chatbots, virtual assistants, NLU (natural language understanding), and Machine Learning and Data Science in general.
How does Ovotor innovate?
Serguei Alechine: We began Ovotor as designers of chatbots and NLU apps, mainly for B2C customer services and corporate internal assistants. But quite rapidly, we had pivoted and focused on a larger market of Data Science and Machine Learning services in the field of fintech. Today our main customers are major banking and insurance groups. We have acted so far as a Data-Science-team-on-demand service provider, designing AI strategies and structuring tailor-made teams for our clients.
Our industry is in constant and high-paced evolution. Since last year we have seen a significant shift: the part of pure data science work in the process of designing AI apps, like model selection and training, is drastically shrinking mainly due to the development and banalization of algorithmic frameworks and Machine Learning Automation what I would call the upcoming “Machine Learning winter.” Now in a production environment, the focus shifts to data preparation, data lakes design, ML pipelines operational management, CI/CD continuous deployment processes, distributed computing, and cloud infrastructures. In short, Data Engineering and DataOps tasks have become more crucial and time-consuming because of increasing amounts of data and the use of more processor-hungry algorithms.
That’s why today, we put our energy and expertise into our clients’ most cumbersome operational workloads like data science pipelines management and continuous integration. Naturally, Ovotor also becomes a provider of MLOps/DataOps and corporate Data Governance consulting services from a data science perspective.
How the coronavirus pandemic affects your business, and how are you coping?
Serguei Alechine: Both our clients and we have had quite turbulent times at the very beginning of it, from March to April. This is because of two factors: our clients have strong data security protocols, hence for many tasks the remote work is not an option, and we are often required to work on-premises inside the client’s data houses; therefore, our cross-regional team was involved in a lot of travel prior the pandemic. But during the first wave, it became crucial to adapt to the new realities: firstly, to relocate a part of our team and onboard new colleagues, depending on geographical requirements.
That was a non-trivial task, but we were up and running at the end of the spring, ready to fulfill all our engagements. We managed to go through that particularly stormy episode mainly thanks to our team members’ right mindset and enthusiasm.
Did you have to make difficult choices, and what are the lessons learned?
Serguei Alechine: Like any organizational change, some vital decisions like team restructuring are not easy, even if they are apparent and imperative. The main lesson we learned is to stay alert, agile, and anticipate any conceivable scenario. This year has shown that Black Swans are quite real.
How do you deal with stress and anxiety?
Serguei Alechine: Many of my colleagues and I are passionate about outdoor sports and activities. I think contact with nature and sunny days, especially if spent with friends and family, are the best way to maintain equilibrium.
Who are your competitors? And how do you plan to stay in the game?
Serguei Alechine: Ovotor plays several roles as a consulting, project management, and recruitment agency and is present in several business segments, so we have to face many different types of competitors. Even our customers’ internal teams could be, for us, a competitor and a partner simultaneously, depending on tasks – such ambiguities aren’t uncommon in the complex tech environments.
Compared to our competitors, we are smaller and more flexible and swift, with a higher level of focus on our primary expertise. In times of a major disorder as the current pandemic, the fastest often win over the strongest. Moreover, we are obsessed with our solutions’ continuous improvement, always going a few steps beyond our clients’ requirements. Sometimes we are criticized by the clients as being too perfectionist and diving too deep into details. Still, in the long run, it appears that we are right in pushing them to invest in the development of more robust and future-proof solutions.
There are three points we stick to stay afloat, pandemic or not: fostering our customer-centricity by identifying the real needs and the root causes of our clients’ issues, being highly specialized in our core subject of Data Science, and continuously innovating by taking any obstacle as an opportunity. In accordance with these principles and our vision of industry evolution, Ovotor is currently developing a SaaS solution for data scientists that should streamline the automation of Kubernetes containerized deployments for ML apps.
Your final thoughts?
Serguei Alechine: This is not the first and not the last crisis we go through. Such times compel us to focus on the essential and review our long-term goals, increase our creativity and resourcefulness, and make more with less. I believe that every upheaval is just another step that accelerates the emergence of more efficient and innovative services and products, resulting in a competitive edge for highly adaptive and ambitious startups like ours.
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