AI-Driven Acceleration of Used Vehicle Price Forecasting

The Customer

Salvador Caetano is one of Portugal’s largest business groups, with a strong international presence in the automotive sector. The group operates in several areas — from automotive distribution and retail to mobility and technological innovation — and is recognised for its constant commitment to modernising and digitising its business processes. This project was the result of a partnership between Devoteam and NiW – IT Services and Consulting, the entity responsible for the digital area of the Salvador Caetano Group.

The Challenge

With the growth of the used vehicle market and its expansion into new international markets, Salvador Caetano faced a critical challenge: the need to constantly update used car prices to maintain competitiveness on digital platforms.

Until then, the traditional pricing process could not keep up with the speed and volume of data required by the business. Furthermore, the constant depreciation of vehicles and market fluctuations necessitated frequent adjustments, necessitating an automated, accurate, and scalable solution.

The Goal

Salvador Caetano’s main objective was to automate used car price forecasting, reducing manual effort, increasing estimation accuracy, and ensuring a competitive market position.

The Solution

Devoteam, in partnership with the Salvador Caetano team, has developed a Machine Learning solution based on the Microsoft Azure cloud platform, which automatically predicts the optimal sale price for each used vehicle.

The solution’s architecture integrated various Azure services, including:

The Methodology

The project began as a Proof of Concept (PoC), which demonstrated the potential of Artificial Intelligence to optimise the pricing process. It subsequently evolved into a production-ready solution, developed in close collaboration between the Devoteam and Salvador Caetano technical teams.

During development, data analysis revealed previously hidden correlations and patterns, enabling the company to gain new business insights. As such, the project not only automated a core process but also added strategic value to the organisation’s collective knowledge.

The Results

With the new solution, Salvador Caetano has been able to:

• Drastically reduce the time needed to update prices;
  
• Obtain more consistent forecasts with an error rate of less than 3%;
  
• Enhance competitiveness across digital sales platforms;
  
• Standardise evaluation criteria across teams and markets;
  
• Gain visibility into previously unknown business patterns;
  

The positive impact was immediate, demonstrating the tangible utility of the solution and ensuring its seamless adoption by the teams.

The Next Steps

The success of the project enabled the expansion of the solution through new add-on modules, ensuring alignment with Salvador Caetano’s evolving business needs.

The solution has demonstrated its resilience to market challenges and has paved the way for future Artificial Intelligence initiatives.

The Conclusion

This project is a clear example of how technology can address real-world business challenges. By combining Devoteam’s technical expertise with Salvador Caetano’s strategic vision, a manual and time-consuming process was transformed into an intelligent, scalable, and results-driven solution.

This success story demonstrates the value of applied Artificial Intelligence within the automotive sector and highlights the role of innovation as a driver of efficiency and sustainable growth.