Product Imagery

In a comprehensive project aimed at streamlining the process of acquiring product images, I developed a sophisticated system to process a list of over 10,000 products. Utilizing the Bing Image API, I automatically generated a collection of potential image matches for each product. To ensure the relevance and contextual accuracy of these suggestions, I implemented an AI-based curation algorithm which vetted the images, achieving an impressive 98% accuracy rate in proposed matches.

To bridge the gap between automation and human expertise, I designed an intuitive user interface that enabled the Product team to efficiently review and select the most appropriate images for their products. This hybrid approach not only significantly reduced the manual effort involved in image selection but also maintained high standards of quality and relevance in product representation. The end result was a seamless integration of technology and user input, culminating in a highly efficient image selection process tailored to the needs of the Product team.