Ferrari Advances Generative AI for Customer Personalization and Production Efficiency
Ferrari S.p.A. · Italy
Ferrari built a car configurator on AWS using LLMs in Amazon Bedrock and Amazon Personalize, letting customers personalize their vehicle across millions of possible configurations with 3D visualization, which increased sales leads and cut configuration times by 20%. Ferrari also fine-tuned Amazon Titan, Claude 3 and Llama models in Bedrock (combined with Amazon SageMaker JumpStart) on its own documentation to power an after-sales generative AI chatbot that classifies and summarizes customer care tickets, and uses Amazon Lookout for Vision to automate quality inspection and defect detection on the assembly line. Generative AI is also used to run vehicle design simulations and text-to-image prototyping to reduce reliance on physical prototypes.
Overview
Ferrari built a car configurator on AWS using LLMs in Amazon Bedrock and Amazon Personalize, letting customers personalize their vehicle across millions of possible configurations with 3D visualization, which increased sales leads and cut configuration times by 20%. Ferrari also fine-tuned Amazon Titan, Claude 3 and Llama models in Bedrock (combined with Amazon SageMaker JumpStart) on its own documentation to power an after-sales generative AI chatbot that classifies and summarizes customer care tickets, and uses Amazon Lookout for Vision to automate quality inspection and defect detection on the assembly line. Generative AI is also used to run vehicle design simulations and text-to-image prototyping to reduce reliance on physical prototypes.
The challenge
Ferrari sought to continue delivering the best possible experiences to customers and dealers while improving their connection with the brand, and to free its teams from managing the infrastructure for its applications.
The solution
Ferrari built a car configurator on AWS, using large language models in Amazon Bedrock together with Amazon Personalize to let customers personalize their vehicle across millions of possible configurations with 3D imagery that can be rotated and zoomed. Ferrari also fine-tuned LLMs in Amazon Bedrock, including Amazon Titan, Claude 3, and Llama, on its own documentation, combined with Amazon SageMaker JumpStart, to train a generative AI after-sales chatbot that classifies and summarizes customer care tickets and answers commonly asked questions. Ferrari uses Amazon Lookout for Vision to spot product defects with computer vision to automate quality inspections and detect missing or defective parts on the assembly line before a vehicle goes to testing. Ferrari also uses generative AI, including text-to-image capabilities, to run vehicle design simulations and prototyping.
Reported business value
Since rolling out the car configurator, Ferrari has increased its sales leads and reduced configuration times by 20 percent. The company has reduced the total cost of ownership for its infrastructure from 70 percent to 40 percent, and can run simulations in its product lifecycle management software 60 percent faster than before.
Sources
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