DetailBuddy’s new AI mobile application resolves a persistent consumer dilemma: selecting optimal foam density for specific paint correction tasks. Using machine learning trained on 250,000+ detailing scenarios, the system analyzes uploaded scratch photos through convolutional neural networks.

Field tests demonstrate 89% accuracy in recommending pad hardness levels, outperforming human experts’ 72% average. The app’s AR mode projects compound application patterns onto vehicle surfaces, reducing buffer burn incidents by 83% among novices. Integration with major brands’ product databases allows real-time chemical compatibility checks. However, privacy concerns emerge as the app collects geotagged vehicle data. “We anonymize all information,” assures developer Marco Silva, noting partnerships with Meguiar’s and Chemical Guys for enhanced troubleshooting algorithms.