Better Product Metadata in Minutes
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.
We’re Experts in Recommender Systems
Alexandra Johnson, CEO
Alexandra has a degree in computer science from Carnegie Mellon University. She started her career working on recommender systems in fashion tech at Polyvore (acquired by Yahoo in 2015), before joining an early pioneer in the ML tools space, SigOpt (acquired by Intel in 2020), where she led the Platform Team. She holds two patents in ML tooling.
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.
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.
