Rubber Ducky Labs
DefunctYC W23San Francisco, US Β· Founded 2022 Β· 2 employees Β· 5 known investors
Rubber Ducky Labs provides AI-based product catalog analysis for e-commerce teams, automatically generating metadata tags from uploaded product data to improve search and discovery capabilities.
Also known as Inc. Β· RDL Β· Rubber Ducky Labs, Inc.
Founders & leadershipΒ· Y Combinator alumni (W23)
Rubber Ducky Labs was founded in 2022 by Alexandra Kissel and Georgia Hong.
Investors Β· 5
Also in the syndicate Β· 3
Funding
SEC filings, press & company announcements- Undisclosed amountSeedJun 2023Source β
Source: company announcements and press reports β follow each round's link for the claim.
Company profile
researched Aug 2026Rubber Ducky Labs, Inc. is a San Francisco-based software company founded in 2022 that built tooling for recommender systems used in e-commerce and other product-discovery contexts. Its initial product was described as operational analytics for recommender systems: a fully hosted web application that connected to a customer's data warehouse to pull custom metrics and data, allowing teams to debug, analyze and improve existing recommendation logic without deploying services, changing code, or replacing their own models.
The product was positioned to answer questions such as why a recommender surfaces seasonally inappropriate items (the company's launch used the example of ski jackets recommended in June). Capabilities cited by the company included visual data exploration with product images, drill-down from aggregate metrics to individual item or user journeys, consolidation and debugging of business logic, annual and seasonal trend views, faceting/segmentation/filtering, and side-by-side comparison of models or ranking changes. Web and API access were authenticated with Auth0.
A later description of the offering emphasizes AI-powered product discovery through better metadata: non-technical users upload a product catalog as a CSV and apply multi-modal AI to tag catalog metadata, with the aim of improving recommendation relevance. The company completed Y Combinator's Winter 2023 batch and raised a $1.5M seed round in June 2023. Y Combinator lists the company as inactive and its founders as former founders.
Founding story
Co-founder and CEO Alexandra Johnson (also cited as Alexandra Kissel) spent roughly eight years in machine learning tooling, including four years as the first software engineer at SigOpt, after earlier work on clothing recommender systems in fashion tech; sources also state she recognized in college that machine learning and data mining could improve shopping experiences and worked at several startups before founding the company. Co-founder and CTO Georgia Hong earned a software engineering degree from the University of Waterloo, completed six internships including at Datadog, Cockroach Labs, Instagram and SigOpt, and then worked on security and ML infrastructure at Meta. They founded Rubber Ducky Labs in 2022 to build the recommender-system tools they wished had existed in their prior roles, developing the product after more than a hundred conversations with practitioners.
Business model
B2B software sold to companies that operate recommender systems. The product was delivered as a fully hosted web application connecting to the customer's data warehouse, with no services to deploy and support for customers' own models; at launch the company was running a private alpha and recruiting design partners rather than describing a published pricing model.
Traction
Reported metrics are limited: a two-person team, a private alpha with design partners, and a first user onboarded in 90 minutes. The company raised $1.5M in seed funding in June 2023 and received coverage from TechCrunch in the same month. No customer counts or revenue figures are disclosed in the sources.
Latest developments
The most recent dated item specific to the company is an October 2024 published video interview with CEO Alexandra Johnson about building an AI recommender-systems company. Y Combinator's profile currently marks the company as inactive and lists both founders as former founders; a third-party profile likewise reports inactive status.
βΈFull profile β market position, technology, go-to-market, geography, history, risks & controversies
Market position
A small, early-stage tooling vendor in AI-driven product discovery and personalization, focused on analyzing and improving customers' existing recommender systems rather than supplying the recommendation models themselves. Backed by Bain Capital Ventures and Y Combinator, with a team of two.
Positioned around making recommender systems interpretable and adjustable by non-engineers: it layers analytics and metadata tooling on top of a customer's existing model and data warehouse instead of replacing the model, offers a no-code CSV upload path to AI-generated metadata tags, and reports rapid setup (90 minutes with its first user) and answers in minutes rather than the days required for ad hoc data science analysis.
Technology
A hosted web app that connects directly to a customer's data warehouse to pull custom metrics and data, supporting visual exploration of recommendation data including product images, drill-down to individual item and user journeys, seasonal and annual trend analysis, faceting and filtering, and side-by-side model or ranking comparisons; customers bring their own model. Authentication for web and API is handled via Auth0. Later product framing centers on multi-modal AI applied to uploaded product catalogs (CSV) to generate metadata tags.
Go-to-market
Founder-led outreach and design-partner recruitment: the company solicited direct email contact from teams operating recommender systems, invited prospects into a private alpha, and used a Y Combinator launch post and referral requests to source conversations. Product development was informed by more than a hundred customer discovery conversations.
E-commerce teams, consumer marketplaces, content discovery platforms and video game companies operating recommender systems; within those customers the intended users are domain experts such as product managers, merchandisers, marketers, growth practitioners and founders, alongside machine learning teams.
Geography
Single reported location: San Francisco, California, United States.
History
Founded in 2022 in San Francisco. The company participated in Y Combinator's Winter 2023 batch and publicly launched its recommender-system analytics product in February 2023. In June 2023 it announced a $1.5M seed round led by Bain Capital Ventures and was covered by TechCrunch. An interview with CEO Alexandra Johnson was published in October 2024. Y Combinator subsequently listed the company as inactive, with Johnson and Hong shown as former founders.
Risks & controversies
The principal recorded risk is discontinuation: the company is listed as inactive on Y Combinator and a third-party database despite having raised seed funding, with no successor entity, acquisition or wind-down explanation given in the sources.
Compiled by commissioned research from 6 cited public sources β announcements, filings, and press listed under research sources below.
Key figures
latest reportedCompany-reported or press-reported figures, each dated to when it was claimed β not independently audited.
Competitors Β· 1
by search overlap
Companies competing with Rubber Ducky Labs for the same Google search keywords, organic and paid, via search-intersection analysis.
Timeline Β· 5
launches, deals, and filingsLaw firm Orrick, Herrington & Sutcliffe published a video conversation between Laura Barr and CEO/co-founder Alexandra Johnson about building a company focused on AI-enabled recommender systems.
Seed round of $1.5 million led by Bain Capital Ventures with participation from Cadenza Ventures and angel investors Brad Klingenberg, Patrick Hayes and Dave Aronchick; proceeds earmarked to expand operations and business reach.
$1.5M source β
TechCrunch article referenced by Y Combinator as the company's latest news.
Public launch of a fully hosted web app that connects to a customer's data warehouse to let teams visually explore recommender-system data, drill from aggregate metrics to individual item or user journeys, debug business logic, view seasonal trends, and compare models side by side.
Rubber Ducky Labs participated in and completed Y Combinator's Winter 2023 batch.
Dated company events from announcements, filings, and press; legal rows summarize public dockets and regulator releases.
In the news
βΈResearch sources Β· 6
primary sources listed
- Rubber Ducky Labs: AI Powered Product Discovery | Y Combinatorycombinator.com Β· web
6 public sources were cited for this profile; the first-party ones are listed here.
Frequently asked questions
- What does Rubber Ducky Labs do?
- San Francisco company building operational analytics and AI metadata tagging tools for e-commerce recommender systems.
- Who founded Rubber Ducky Labs?
- Rubber Ducky Labs was founded by Alexandra Kissel, Georgia Hong in 2022.
- Who are Rubber Ducky Labs's investors?
- Rubber Ducky Labs's investors include Y Combinator, Bain Capital Ventures.
- Where is Rubber Ducky Labs headquartered?
- Rubber Ducky Labs is headquartered in San Francisco, US.