An evaluation study of AiLoupe: An AI driven design tool to source and select textile materials

Abstract

Designers typically source materials physically in expos, collections, and shops, relying on their touch and tacit knowledge. Whilst effective, this process faces challenges such as time constraints, inefficiency, and limited transparency. Amidst a rise in new digital tools to aid in textile material selection, there is a gap in evaluation studies of how these tools contribute towards the designer’s Material Sourcing Journey (MSJ), particularly taking into account the sensory experience of materials. This paper presents a study involving 22 textile, fashion and product designers to evaluate AiLoupe, a mobile app which uses image recognition and a purpose-built Sensory Materials Library to aid designers to identify, select, and source materials in the studio and at fabric expos. Results highlight AiLoupe’s potential to streamline workflows, support sustainability, and improve collaboration through its structured Material Data Cards (MDCs). Insights emphasize designers’ need for comparison tools, clearer performance scales, and enhanced accuracy of physical material identification.