what we offer
understand.
act.
grow.
We analyze your business and data landscape to identify and valuate unexploited data opportunities.
We develop, implement and run tailormade AI-driven projects that generate measurable value for you.
We continuously operate and further improve all AI components after their launch.
We provide a fresh perspective, either case by case or on the level of an actionable AI roadmap.
We serve as a change agent to allow for the successful transformation of your end-to-end processes.
As a trusted partner we ensure that business insights from the models are available at your fingertips.
what we offer
understand.
We analyze your business and data landscape to identify and valuate unexploited data opportunities.
We provide a fresh perspective, either case by case or on the level of an actionable AI roadmap.
act.
We develop, implement and run tailormade AI-driven projects that generate measurable value for you.
We serve as a change agent to allow for the successful transformation of your end-to-end processes.
grow.
We continuously operate and further improve all AI components after their launch.
As a trusted partner we ensure that business insights from the models are available at your fingertips.
who we are
Proxinea is a Swiss Startup based in Zurich, Switzerland. The two founding partners, Felix Reisen and Bernard Bertschy have worked with each other for many years in the area of Business Intelligence and Artificial Intelligence (AI). Both gathered in-depth experience over time on how to use these advanced techniques most efficiently to change the status quo and exploit hidden potential. In 2021, Felix and Bernard decided to found Proxinea to help midsize to large companies lift their capabilities in the area of Data Science, Machine Learning and Artificial Intelligence.
Bernard Bertschy
CEO & Founder
Bernie is the navigator of Proxinea. His years of experience in top Finance and Business Intelligence management positions allow him to attentively find the right spots where to invest to get better results. His emphatic leadership style is a catalyst to introduce change.
Besides work, Bernie loves to spend time with his family and is a passionate golfer and sailor.
Bernie studied economics and holds an Executive MBA from University of Zurich.
Dr. Felix Reisen
COO & Founder
Felix is the data science brain of Proxinea. He has an excellent feel for data and many years of experience in how machine learning can be successfully applied in companies. Over the last decade, he has executed data science projects with marketing, sales, technology and research departments from various industries.
Besides work, Felix loves to play the piano and is a passionate cook for friends and family.
Felix holds a Doctor of Sciences from ETH Zurich and a Diploma in Bioinformatics from the University of Frankfurt.
Dr. Gautam Munglani
CTO & Partner
Gautam is the tech meister of Proxinea. His specialty is in building the algorithms and infrastructure that underly our data science solutions. He combines this deep technical expertise with an uncanny knack for generating business value. Previously, he was engaged in new product development in the Telecom, Research, and Health Startup industries.
In his free time, Gautam loves to hike in the mountains and experiment with various types of food.
Gautam holds a Doctorate in Physics from ETH Zurich as well as Bachelor’s and Master’s degrees in Engineering from Georgia Tech and TU Eindhoven.
Youssef Janjar
Senior Data Scientist
Youssef Janjar is a skilled Data Scientist with a proven track record of transforming unstructured data into valuable insights and data products for a range of industries. With a strong foundation in computer science and strong knowledge in cloud computing and data visualisation, he has spearheaded several successful data science projects. His talent for storytelling allows him to communicate complex ideas and data-driven insights in a clear and compelling manner.
During his spare time, he relishes the opportunity to hit the football field or immerse himself in the latest album releases.
Youssef holds a Master's degree in Data Science from EPFL Lausanne and a Bachelor in Computer Science.
Dr. Anna Kutschireiter
Senior Data Scientist
Anna is a seasoned data and machine learning scientist with strong expertise in developing robust and rigorous ML algorithms. With a solid academic foundation and a specialization in mathematical modeling, she has successfully led collaborative research ventures and projects in both academia and industry.
Beyond her professional pursuits, she finds joy in baking visually stunning cakes, long hikes, and swimming across lakes.
Anna completed a prestigious postdoctoral fellowship at Harvard University, holds a PhD in Computational Neuroscience from the University of Zurich, an MSc in Theoretical Physics from the University of Heidelberg, and a BSc in Physics from the University of Frankfurt.
Matthieu Burguburu
Data Science Intern
Matthieu is an enthusiastic Intern at Proxinea. He is driven by a passion for leveraging technology to solve complex problems. He focuses on applying cutting-edge LLM techniques to advance our data science capabilities in this particular area.
Outside of work, he enjoys the thrill of rock climbing and the tranquility of sailing.
Matthieu is currently pursuing a Master's degree in Computer Science at EPFL specializing in Data Science and Machine Learning. He holds a Bachelor’s degree in Computer Science from HEIG-VD (Switzerland).
Mikio Oba
Senior Data Engineer
Mikio is a seasoned data engineer with over twenty years of experience. His expertise and problem-solving skills drive his success in creating data systems that support critical decisions and deliver insights. He focuses on ensuring data infrastructure reliability, scalability, and efficiency.
Outside of work, Mikio enjoys photographing architecture and landscapes, and appreciating the subtle art of modern Swiss typography and visual design.
Mikio holds multiple Master’s degrees, including one in Aeronautics from the University of Tokyo (Japan) and another in Information Systems from the University of Sheffield (UK).
Andreas Nord
Data Engineer
Andreas is an engineer with broad experience in the data space. Various roles in data engineering and software engineering have provided him with a comprehensive overview of all components involved in building successful data products. His previous industry experience includes projects in the fields of autonomous driving and neuroscience.
In his free time, Andreas enjoys a variety of sports activities such as climbing and snowboarding, as well as creating jazz/fusion music.
Andreas has a Master’s degree in Engineering Mathematics from Lund University (Sweden).
Unlock your data’s untapped potential
Have you ever thought about how much information is hidden in your unstructured data?
Unstructured data is everywhere, and it is full of information. Consider, as an example, recordings of customer calls. They can reveal the sentiment of your customers – are they happy? Are they complaining? What are they complaining about? Are they close to leaving, or can you sell them another product?
When you read the transcript as a human, you know exactly how to extract these types of information from the calls. But human time is limited, and manually extracting this information takes a lot of time, in particular for high call volumes.
With the use of large-language models (LLMs), it is possible to answer these questions in a fully automated manner, and at scale.
These models can be used to extract exactly the information that you need, which can then be used to gain valuable insights at a large scale.
We make the most of your data, structured and unstructured, and turn this into measurable customer value.
Prioritize customer lifetime value over quick sales
Have you ever had the feeling that sales numbers look good on paper, but still something seems off?
Many companies experience this “free fall” without noticing it: short-term boosts in sales hide long-term declines in customer value. Discounts, aggressive campaigns, and one-off conversions create quick wins, but they rarely build durable relationships. In fact, they can even accelerate churn.
When you take a step back and follow the broader customer journey, the picture becomes clearer. Not every conversion is equal. Some customers bring value over years; others stay for a single contract cycle and then disappear. And the difference between the two can be dramatic for your bottom line.
Modern machine-learning models make it possible to quantify this difference precisely. They predict which customers are likely to stay, who is at risk of leaving, and which products make sense for which profiles. Suddenly, selling becomes less about “catching the next contract” and more about steering towards long-term value.
By shifting from transactional thinking to customer-lifetime thinking, companies can stabilize their customer base, reduce churn, and grow sustainable revenue, without falling into the trap of constant short-term optimization.
We help you identify the customers that matter most, personalize offers that keep them engaged, and turn long-term value into your competitive advantage.
Price with data, not instinct
Finding the right prices or having the ‘guts’ to change them is a big challenge.
It's a delicate balancing act where pricing too high can lead to customer loss, while pricing too low can result in missed profit opportunities. So what is best practice?
By leveraging your own data, such as analyzing historical sales data, studying customer behavior, and monitoring market trends, you actually can determine the optimal price point for your products or services. This involves understanding price elasticity, which measures how demand responds to changes in price.
With the help of data science techniques, the optimal price points can be derived to maximize revenue and profit margins while keeping you competitive in the market.
So, if your pricing decisions have been based on intuition alone, it's time to incorporate data science into your strategy.
Use data to push beyond the status quo
We noticed a common trend among companies: a dedication to professional and finely-tuned value creation. This dedication stems from their years of experience and success in the market, where they've already optimized everything possible with their existing tools, techniques, and knowledge. However, in today's age of AI and machine learning, there's a chance to elevate these processes even further.
Refining current methods with advanced techniques fosters genuine optimization through collaborative innovation and expertise from both sides.
How can you ensure your investment yields returns? Conduct AB tests wherever feasible. These tests offer tangible results by comparing value creation before and after AI integration. Once validated, seamlessly implementing these techniques becomes the next step toward realizing your envisioned value.
It's a journey of continual improvement, fueled by cooperation and innovation. Interested in exploring the possibilities?
Replace assumptions with data-driven simulations
While Excel will survive for many more years, it's evident that its approach has its constraints. Embracing the future involves utilizing all available data to uncover hidden patterns and drive superior outcomes.
To complement their traditional planning scenarios, many companies have started using AI-driven forecasting. Why the shift? Because it enables businesses to run complex simulations, make the most of available data, and spot changing patterns. When paired with predictive models like NEXT BEST OFFER/ACTION (NBO/A), its capabilities become even more powerful, bringing you closer to understanding and predicting customer behavior.
The magic lies in the ability to simulate "what if" scenarios which provide answers in probabilistic terms to guide decision-making at precisely the right moments. It's about moving beyond gut feeling and restrictive Excel forecasts. By embracing unbiased forecasting and probabilities, you align your decisions with a more nuanced understanding of the data. Make the shift now and elevate your decision-making process!"
We at Proxinea are a team of experts with proven track records of optimizing customer value by leveraging artificial intelligence.
Identify customer preferences based on data
For some it may work. Others use NBO. Next Best Offer (NBO) is a personalized marketing solution that actively steers and manages your customer base. It supports sales & marketing activities for every customer touchpoint and yields higher profits compared to untargeted offers.
NBOs address challenges faced by subscription-based businesses offering complex price/product combinations. Without personalized offer selection, customers often miss out on the latest products and frequently pay uncompetitive prices leading to churn. Managing this complexity is a struggle for most companies.
The solution is to use Machine Learning models (ML) to select products matching the needs of the customers and offering them at a personalized price.
From our experience, when executed properly, ML-driven NBOs increase value generated through sales into the customer base by 50-100%, thereby enhancing customer satisfaction and reducing customer care interactions.
