Sortwell represents an innovative approach to addressing recycling confusion through artificial intelligence integration. Developed by Ridwell, the application leverages machine learning algorithms to analyze plastic items and provide immediate sorting recommendations, positioning itself as a practical tool in the sustainability technology sector. The core functionality revolves around image recognition technology that processes photographs of plastic items against a trained database. Users place items on a neutral background, capture an image through the application's camera interface, and receive instant classification results indicating the appropriate recycling stream. The system reportedly handles various plastic types including film, rigid containers, and multi-layer packaging (MLP) with varying degrees of accuracy depending on lighting conditions and item distinctiveness. User experience centers on minimalistic design with a single-button operation model. The interface prioritizes simplicity, requiring minimal technical proficiency while maintaining rapid processing times. Real-world testing indicates optimal performance occurs with well-lit, clearly identifiable items placed against contrasting backgrounds, though performance may vary with unusual shapes or heavily worn materials. The absence of historical tracking or saved scans represents a notable gap in functionality that could enhance utility for frequent users. User feedback consistently highlights the application's effectiveness in resolving common recycling uncertainties. Carri Urbanski noted on August 13, 2025: 'This has taken the guess work out' of distinguishing between plastic film and MLP materials. Multiple reviewers have echoed the desire for expanded functionality including scan history preservation and reference libraries for frequently recycled items, suggesting areas for future development. The application demonstrates significant strength in solving specific identification challenges but faces limitations regarding comprehensive plastic recognition and data persistence. Ideal usage scenarios involve household recycling situations where users encounter occasional uncertainty about proper plastic disposal methods, particularly with complex packaging materials that challenge conventional recycling knowledge.