Web Analytics

3 Latest Announced Rounds

  • $10,500,000
    Unknown

    3 Investors

    HVAC and Refrigeration Equipment Manufacturing
    Nov 5th, 2024
  • $4,000,000
    Series A
    Financial Services
    Nov 5th, 2024
  • $9,500,000
    Seed

    4 Investors

    Software Development
    Nov 5th, 2024
$1,416.01M Raised in 71 Funding Rounds in the past 7 Days - View All

Funding Round Profile

Rubber Ducky Labs (YC W23)

start up
United States - San Francisco, CA
  • 26/06/2023
  • Seed
  • $1,500,000

Rubber Ducky Labs builds Operational Analytics for Recommender Systems. We build tools to debug, analyze, and improve recommender systems, allowing machine learning teams to move faster on projects that have a direct impact on the company’s bottom line


Related People

Alexandra JohnsonCo Founder

Alexandra Johnson United States - San Francisco, California

My mission is making it effortless to use the state of the art in machine learning, while cultivating a positive and inclusive company culture.

I'm the co-founder and CEO of Rubber Ducky Labs, which builds operational analytics for recommender systems.

We build tools to debug, analyze, and improve recommender systems, allowing machine learning teams to move faster on projects that have a direct impact on the company’s bottom line.

If your company is recommending products to your users - whether e-commerce, media, gaming, etc - we'd love to chat!

I've been a founding team member of two MLOps startups, Gantry and SigOpt, and prior to that I worked in fashion tech, shipping products for Rent the Runway and Polyvore. Over my time at half a dozen different startups, I've grown to love exploring the psychology of how users choose to adopt (or not adopt) AI / ML tools and platforms.

I believe strongly in contributing back to your community, and for almost five years I led the 6500+ member Bay Area chapter of Women in Machine Learning and Data Science (WiMLDS). Under my leadership we hosted 150+ events, 30 people volunteered with our chapter, and we launched a mentorship program, a blog, and our #MachineLearningMonday newsletter.