Are you struggling to use your data with multiple, incompatible software and tedious manual work? You are not alone. With increasing amounts of collected data, many e-commerce and retail companies struggle to sync, understand and use their data with black-box solutions or incompatible tools.

Building on our research, we have developed tools that can revolutionize your work by making it simple and rewarding to turn complex data into meaningful actions. With our flexible solution that seamlessly syncs your data, integrates with your existing marketing ecosystem, and helps you automatically identify and trigger marketing activities, you will get new insights, grow your business, and save hours from your workday.

We understand that you don't want to add another tool to your marketing technology stack. The complexity is already high, and how could one more tool make it easier to understand your customers better and turn these insights into value-creating activities?

That's why we have put our souls in building a flexible solution that integrates with your existing marketing ecosystem. The AI-powered platform transforms your transactional data into insights about your customers and their behaviors. To avoid having to export these insights into a new tool, we automatically identify desired actions based on the generated insights. To make it simple, we connect to your marketing channels with an API, so the insights convert to actions that drive your growth.

And to make it risk-free for you, you can test before you commit to a long-term solution. Our POC will give you a clear understanding of how much value we will generate to you.

Book a free demo to see how we can help you acquire new skills, be more productive, and exceed your goals.


[ in-foh-buh-leen ]

Infobaleen derives from information and baleen, the filter-feeder system inside the mouths of baleen whales. Infobaleen allows you to effortlessly sift knowledge from oceans of data and turn them into valuable actions.

We are passionate about helping you with your interaction data

The most rewarding data describe how things connect over time. For example, from the patterns of how people and products connect in dynamic consumer networks, we can predict how the system will evolve. Revealing the inner workings of interconnected systems is the core of network science and the heart of our passion for interaction data.

Academic research

For Martin the love for interaction data came true when he, after his Ph.D. in network science at the legendary Niels Bohr Institute in Copenhagen, moved to the University of Washington in Seattle to do his postdoc in 2006. There he started working on a grand challenge in network science: how to simplify and highlight essential regularities in networks into maps. Mapping networks is a holy grail of data science because in the myriad links and nodes of a network hide answers to how we can predict how the system will evolve. For example, who has a high risk for cancer in who will buy what next in a consumer network?

Based on information theory, we took a novel and advantageous approach to mapping networks. But coming up with the underlying math was not enough. Mapping large networks also requires efficient algorithms. And comprehending and communicating the results requires compelling visualizations such as our innovative alluvial diagrams for mapping change over time. Most researchers focus on one of the three aspects, the math, the algorithms, or the visualizations, but we decided to go for all of them. It has paid off. Because when the right math, algorithms, and visualizations came together and worked in synergy, we immediately started making exciting discoveries in complex interaction data.

After we had shown maps of science and how it changes over time in ways that nobody had seen before, we soon received requests to help other researchers make good maps of their interaction data. We realized that we needed powerful tools for automating the process of going from raw data to insightful maps and discoveries. From 2009 at Umeå University, Martin started working with Daniel, who built the first interactive map and alluvial diagram generators. At the same time, Andrea's benchmark tests showed that our algorithms outperform other approaches. As a result, thousands of researchers have used our software available on Moreover, the broad interest in our tools has allowed us to collaborate with many different researchers in exciting projects, including mapping change in the overnight money market with researchers from the Federal Reserve Bank of New York.

Building a team to help you

When Andrea joined our research team in 2014 after his postdoc at Northwestern University, we reached a critical mass of skills. With his landmark work on data-driven algorithms and skills to build interactive visualizations of large data sets such as Wikipedia and IMDb, we decided it was time to let people outside of academia benefit from our research. We were fortunate to team up with Jakob and Niklas, who, thanks to over 15 years of experience in media, e-commerce, and international business, has established the essential link between our research solutions and the industry data challenges.

By recruiting Christian, John, Florian, and Johan, who complement our skills for maximum productivity, and establishing a direct link with our interdisciplinary research in IceLab, we can realize our goal: Flexible tools that help you automatically identify and execute activities that grow your business and save hours from your workday. If you are struggling to use your data with multiple, incompatible software and tedious manual work, our tools can revolutionize your work by making it simple and rewarding to turn complex data into meaningful actions

Book a free demo to see how we can help you acquire new skills, be more productive, and exceed your goals.

Who we are

Jakob Sjölander

Chief Executive Officer (CEO)

Daniel Edler

Data scientist

Andrea Lancichinetti

Chief Product Officer (CPO)

Christian Persson

Chief Technology Officer (CTO)

Martin Rosvall

Chief Science Officer (CSO)

John Bergman

Software developer

Florian Uekermann

Data scientist

Johan Lilljebjörn

Sales manager