AI Powered Product Discovery
We built Rubber Ducky Labs to help e-commerce teams effortlessly improve product discovery through better metadata. Our tool enables non-technical users to leverage multi-modal AI on product catalogs—just upload a CSV and start tagging metadata in minutes.
Our Team
Alexandra Johnson, CEO
Alexandra’s career spans half a dozen startups over multiple industries. She started in fashion tech, working on recommender systems and search at Polyvore (acquired by Yahoo in 2015), before joining the ML tools space on the founding team at SigOpt (acquired by Intel in 2020), where she led the Platform Team. She holds two patents in ML tooling, and has a degree in computer science from Carnegie Mellon University.
John McDonnell, CTO
John led the recommender systems ML group at Stitch Fix and has built transformative ML solutions spanning risk, recommender systems, and paid acquisition at Square (now Block) and Stitch Fix. His PhD from NYU is in Cognitive Science with a focus on computational modeling and holds one patent in recommender systems.
Our Design Partners
Unlimited Use Cases
Rubber Ducky Labs makes accurate metadata abundant. Our web app guides you through setting up AI labeling tasks so you can get initial results in seconds.
Search: Expand culturally relevant keyword coverage.
Recommendations: Recommend seasonally appropriate items.
Marketing: 100x your whimsical campaign creativity.
SEO: Boost rankings with thousands of category pages.
