Probuss

Probuss is a Berlin‑based data analytics company that specializes in probabilistic modeling for transportation logistics and supply chain optimization. Founded in 2018 by a group of data scientists and former logistics managers, the company has developed a suite of software tools that use Bayesian inference and machine learning algorithms to forecast demand, optimize routing, and assess risk in real‑time.

The core product, Probuss Core, is a cloud‑based platform that ingests sensor data from fleets of vehicles, warehouse inventories, and external market indicators. Using a combination of Markov chains and Gaussian processes, the platform generates probabilistic predictions about delivery times, fuel consumption, and equipment failure rates. Clients can integrate Probuss Core via RESTful APIs or a proprietary SDK, and the solution supports multiple industry verticals including freight forwarding, perishable goods distribution, and autonomous vehicle fleets.

In addition to its standard modeling tools, Probuss offers consulting services that help organizations build custom analytic workflows and train staff on advanced probabilistic programming techniques. The company emphasizes transparency by providing visual explanations of model uncertainty and marginal contribution of individual variables.

By 2023 Probuss had secured three rounds of funding, raising a total of €25 million, and had entered partnerships with several large shipping carriers and urban logistics startups. In 2025 the firm released an open‑source library, Probuss‑Py, to foster a community around reproducible probabilistic analytics. While still privately held, Probuss has positioned itself as a niche provider of data‑driven decision support in a market traditionally dominated by deterministic optimization tools.