Our proprietary AI was first built by Simon during research work focused on lasting challenges met by purchasing departments in large manufacturing companies, conducted at ETHZ (Swiss Federal Institute of Technology) under the guidance of Prof. Dr. Stephan Wagner, chair of Logistics Management department.
Simon soon joined forces with Arnaud, who had launched and managed a media company beforehand, to give life to GenLots and optimize industrial purchasing, making replenishment simple and efficient.
Academic roots, industrial impact: The GenLots story
Our story
A Swiss supply chain tech startup
Our technology
A machine that learns to optimise hard trade-offs
Most ERPs optimise one variable at a time. GenLots optimises all variables simultaneously — quantity, timing, discounts, waste, carrying cost — in a single reinforcement learning algorithm. The result is a supply plan that reflects the true total cost of every purchasing decision.
To find it, the algorithm explores a solution space almost as large as the number of atoms in the universe. It learns which strategies lead to the optimal plan, squaring every trade-off automatically. Not only does this deliver cost savings with astonishing results — it is also extendible to include factors such as CO2 emissions in its model of the world.
Our people
Discover the people behind GenLots
