Transport sector
Transportation
The transportation sector is being redefined by the need for more sustainable and efficient solutions. QUANT AI Lab provides innovative technologies to: route optimization, fleet management, security and predictive maintenance, smart mobility.
Route Optimization
Our solutions analyze data in real time to optimize transportation routes, reducing costs and improving the punctuality of deliveries.
Fleet Management
We offer tools to monitor and manage vehicle fleets, increasing operational efficiency and reducing downtime.
Safety and Predictive Maintenance
We implement predictive maintenance systems that identify and address potential problems before they occur, ensuring safety and prolonging the useful life of assets.
Intelligent Mobility
We develop solutions to improve urban mobility, from traffic management to the development of autonomous vehicles.
View use cases
Linking carton, scan & weights data
As part of its Data & AI transformation, a French transportation and logistics company providing land, sea, and air solutions to and from 157 countries, aims to enhance internal processes, with a focus on improving the performance and productivity of operational teams, particularly in warehouse management and trucking.
Generative AI travel assistant
GPTravel utilizes advanced AI technologies to deliver tailored travel and flight recommendations based on individual user preferences.
Purchase Propension model
The system uses advanced machine learning to analyze digital interactions from Google Analytics and comprehensive CRM data, improving the accuracy of purchase propensity predictions.
Explanatory drivers of NPS
The tool aims to measure and explain the impact of various variables on the Net Promoter Score (NPS), a key performance indicator (KPI) for the company. NPS is calculated by evaluating the probabilities of clients being promoters or detractors.
Data transformation for IT urbanization
As part of its 2020 IT urbanization strategy, our client, a major player of the transportation sector, sought support in defining and implementing a distributed governance model.
Destination recommender system
The system uses advanced machine learning to parse travel history and preferences from Google Analytics and CRM, improving recommendation accuracy. Targeted web banners based on these recommendations aim to increase booking likelihood at key decision-making moments.
Web sales forecasting
The project arises from the business need to have an estimation of web sales in advance to anticipate strategic decisions for the company. From there, 2 objectives were set: the first being a monthly sales forecasting model to predict three months ahead, and the second being a daily sales forecasting model to predict 30 days ahead.
