Using Machine Learning, Wise automatically schedules, monitors, and adjusts routes in real time, ensuring the most efficient routes, and all while considering multiple variables and constraints. Wise continuously learns from fleet data, helping optimize and improve fleet performance over time.
Serving numerous industries -- food and beverage, business services and products, field service technicians for cable and utilities, 3PL and more -- Wise is proven to give management teams unparalleled visibility and control over operations, while helping drivers improve their on-time performance and account service. Wise customers usually migrate from static routing systems or classic planning methods, using Wise alongside their previous systems for dynamic routing, then rapidly implementing additional modules.
Started out of MIT by a team with deep expertise in logistics, data science, machine learning, and design, the Wise team has always shared a focus on solving mobility issues by understanding patterns. In fact, in the early days of the company, the founders spent more time asking for data than investment, but that turned out to be a very good decision.
At Wise, we love what we do -- helping customers!
Powering the Future of Logistics
With deep expertise in logistics, data science, machine learning and design, and a strong commitment to solving global mobility issues, Wise Systems is preparing global delivery and logistics operations to meet the demands of an increasingly dynamic future economy.
Diverse, Multidisciplinary Team
Wise Systems was founded by a highly accomplished team with expertise across logistics, software, design and business. The result is a hard-working team that takes pride in delivering innovative solutions to some of the logistics industry's biggest challenges.
The key to always improving fleet performance lies in machine learning, which continuously optimizes delivery routes based on analyzing and learning from all available data. The result? Efficient, on-time deliveries with dramatic reductions in miles driven and merchandise refusals.