Wise Systems

Wise Systems is a Cambridge, Massachusetts company that develops an AI-driven routing and dispatching platform for last-mile delivery and service fleets. The platform is modular and organized around the Wise Systems Dynamic Optimization Engine (DOE), which combines a customer's delivery priorities and constraints with real-time traffic data, historical weather data, road closure information and established traffic flow patterns to generate and continuously adjust routes. Role-specific applications sit on top of the engine and can be deployed independently or together, and can be integrated with existing systems of record on an a la carte basis via an Engine API.

The application suite covers planning, execution, and analysis. Strategic Planner is a web-based tool for modeling the optimal number of vehicles, drivers, delivery frequencies and territories, and includes Network Optimization for redistributing customers across warehouses in multi-depot operations. Route Planner calculates optimal routes for static, dynamic or hybrid routing with support for zoning, on-demand orders and time windows. Dispatcher lets teams push routes to drivers, monitor loads and driver progress in a live map view, and re-sequence routes during the day. The Driver mobile app (iOS and Android) provides interactive route lists and maps, turn-by-turn navigation, proof of delivery via barcode scanning, photo capture and eSignatures, plus notes and parking pins that capture driver knowledge for reuse. Customer Portal gives delivery recipients real-time ETAs, tracking and opt-in notifications via SMS or email links; Mobile Manager and Mobile Merchandiser apps push status to managers, merchandisers and field reps; and Performance Manager reports planned versus actual mileage, travel time and on-time percentage by driver, depot and day.

The company describes its approach as autonomous dispatch and routing: machine learning models observe how an operation actually works, learn service times and route-specific behavior, and automatically schedule routes, monitor them in progress and adjust to day-of delays.

Founding story

Company press releases state Wise Systems was founded in 2014 by a group of MIT and Harvard graduates around the idea of using data to transform how goods and services move in cities. MIT Media Lab lists Wise Systems as a Media Lab spinoff that grew out of an MIT class project, and CEO Chazz Sims previously worked in the Media Lab's Human Dynamics Lab. (Note: sources give a 2014 founding date, which differs from the 2013 date held internally.)

Business model

Wise Systems sells a modular business software platform to fleet operators. Customers can adopt individual role-based applications and add more over time, with configurations ranging from manual data input/output to full automation and integration with existing systems via the Engine API. The platform has also been made available through the SAP App Store, and is distributed to commercial vehicle customers in Japan through a partnership with Mitsubishi Fuso Truck and Bus Corporation.

Traction

At the time of the 2018 Series A, the company said it was powering transportation operations in more than 50 locations and across thousands of drivers nationwide, serving customers from multi-billion-dollar enterprises such as Anheuser-Busch to regional operators. In the October 2021 Series C announcement, the company reported 300% year-over-year growth over the prior two years and cited customers including Anheuser-Busch and Lyft. Marketing materials cite customer results of up to 15% fewer fleet miles, an 80% reduction in late arrivals and 20% higher fleet utilization.

Latest developments

The most recent developments documented in the sources are the October 2021 $50 million Series C led by Tiger Global Management, the 2021 Mitsubishi Fuso partnership for the Japanese market, and availability in the SAP App Store. The current website describes expanded product modules including Strategic Planner with Network Optimization for multi-depot operations and Performance Manager for planned-versus-actual fleet analytics.