Case studies

How the Aisin Group collaborated with Montreal-based startup Funartech to solve its logistics challenges

Looking for innovative ways to optimize the routes of its fleet and improve the overall efficiency of its logistics, the Aisin Group, a major Japanese supplier of automotive parts and systems, and a Fortune Global 500 company, turned to an accelerator to scout the most innovative startups in Canada. Route planning poses several challenges to speed, accuracy and predictability, creating inefficiencies in key business areas, which can be revolutionized with the power of artificial intelligence.

Corporate-startup collaboration is key to accelerating the innovation cycle

The project was designed to generate a win-win partnership between a large corporate and a selected startup while accelerating its growth. It’s easy to see how this type of partnership benefits both parties: startups have the opportunity to secure a major commercial agreement with an international company, while corporations need to solve concrete business challenges and stay ahead of the curve with the latest technologies.

The accelerator provided strategic support and guidance to reduce the risks of such collaboration by validating the feasibility and viability of a proof-of-concept. Of the 800 startups scouted, over 50 were interviewed and invited to submit business proposals, which were methodically evaluated. After vetting, prioritizing, and several meetings, the Montreal-based startup Funartech, which combines machine learning and operations research, was ultimately selected for a proof-of-concept alongside the Japanese supplier of automotive components.

A successful collaboration

The collaboration between Funartech and the Aisin Group has been smooth. The proposed challenge is a very difficult one that implies a lot of factors to take into account and thus a very high complexity. Not to mention that, as expected with such a corporation, the instances to solve are quite large. Fortunately, the Aisin Group trusted Funartech's vision and new way of doing AI to solve their problem. Funartech proposed its hybridization of machine learning and operations research to solve it not only theoretically but also in practice. After six months, this fruitful collaboration lead to the creation of a first prototype that is able to reduce by 30% the number of trucks needed to deliver parts between Aisin’s warehouses. The optimization part of this first prototype essentially uses approaches from Operations Research, a science of optimization that deserves more recognition. Funartech collaborated with Pr Michel Gendreau from Ecole Polytechnique of Montreal, a world-known expert in the field who has been a key player in the development of the solution.