ABOUT US

At Mnubo, we put innovation and customer value at the heart of everything we do. Our world-class team of Data Scientists and AIoT Experts work cross-functionally to break down silos and get to know the people and the problems behind the data. Our products go beyond remote monitoring and control. They improve operations, enhance productivity & efficiency, and boost customer service.

Our Story

It all started in 2011 in Montreal, Canada, when Frederic Bastien, Jean-Christophe Cimino, Aditya Pendyala and Jean Charles Beaudin had a vision. After several years of building databases for telecom and M2M service providers, they began to realize that the M2M space was transforming into a data-rich IoT ecosystem. They also realized that while devices could be located and identified, sensor data generated by these devices could not easily be managed.

They started thinking of a fundamentally new way to process and leverage sensor data, one where all companies could turn to their IoT data to answer the toughest business problems, and one that would challenge traditional manufacturers to shift from a hardware-driven business model to a data-driven mindset. Mnubo was born.

IoT has now entered the mainstream, and Mnubo created one of the very first analytics solutions built solely for its data. The expertise we have built over the years, as well as our relentless commitment to solving the most challenging business problems, has helped us build a loyal customer community across a variety of verticals.

Today, Mnubo employs more than 60 data experts dedicated to helping our customers. Headquartered in Montreal, Mnubo also has satellite offices in Japan and South Korea.

Mnubo’s SmartObjects solution provides AI & IoT Data Analytics to help product manufacturers build better-connected products and services.

Mnubo’s solution equips manufacturers with insights that allow them to improve product usage, increase customer engagement, reduce customer churn and lower the cost of operations. SmartObjects facilitates the exploration and analysis of sensor time series and events in order to obtain insightful and actionable information about connected products, enabling ‘connected things’ to become ‘smart things’.