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Chicisimo is a remote-based technology company that originally developed a smart virtual closet application for women before pivoting to a B2B software model. The consumer platform allowed users to digitize their wardrobes and receive machine learning-driven outfit suggestions, ultimately reaching four million active female users and generating over five million total application installs. After executing 204 updates on the Apple App Store, the consumer application was shut down in December 2019 to focus entirely on enterprise solutions. The company now licenses its underlying data infrastructure to global fashion retailers through the Fashion Taste API, providing automated taste profiles and product recommendations. Operating with a remote team of eight employees, the enterprise secured $800,000 in seed funding backed by angel investment firm VitaminaK. Chicisimo was originally founded in 2010 by entrepreneur Gabriel Aldamiz-Echevarría and his wife.
Chicisimo has raised $800K across 1 funding round.
Chicisimo has raised $800K in total across 1 funding round.
Chicisimo has raised $800K across 1 funding round. Most recently, it raised $800K Seed in July 2012.
| Date | Round | Lead Investors | Other Investors | Status |
|---|---|---|---|---|
| Jul 11, 2012 | $800K Seed | Vitamina K | — | Announced |
Chicisimo has raised $800K in total across 1 funding round.
Chicisimo's investors include Vitamina K.
Chicisimo was a technology company that developed AI-driven tools for the fashion industry, centered on a smart virtual closet enabling users to digitize clothes and receive personalized outfit recommendations.[1][2][3] It served women consumers via iOS and Android apps (reaching 4-5 million installs) and later pivoted to B2B offerings like the Fashion Taste API for retailers to build taste graphs and personalization infrastructure.[2][5] The core problem solved was capturing and automating "what-to-wear" advice from unsupervised learning on user closets, outfits, and interactions, boosting retention through ontology, taste graphs, and recommenders—though consumer apps shut down in December 2019 amid acquisition search, with tech offered as-a-service post-2020.[1][2][5]
Founded by Gabriel Aldamiz-Echevarría, Chicisimo emerged from a vision to mirror Spotify's listening behavior capture but for fashion, automating outfit advice via disciplined ML on real-user data.[1][5] The team built an unsupervised learning model classifying clothes and inferring taste from closet uploads, queries, and interactions, starting with consumer apps that digitized wardrobes in minutes and suggested combinations or real-woman outfits.[1][2][3] Early traction hit 4 million women users through vertical ML, earning 5-star ratings and Apple features, with a fully remote 8-person team emphasizing culture; pivotal shift came in 2019 when standalone operations ceased, leading to post-mortem and API pivot for retailers.[1][2]
Chicisimo rode the AI personalization wave in fashion retail, timing into rising e-commerce and omnichannel demands where taste data creates moats amid commoditized products.[2][5] Market forces like shopper-generated data explosion favored its Taste Graph, influencing ecosystems by open-sourcing consumer-honed tech (e.g., APIs for retailers) and patents that enable "shop the look" and trend intelligence, pushing competitors toward data-owned personalization over third-party reliance.[1][5] It highlighted vertical ML's power in niche domains like fashion, paving for post-shutdown integrations.
Post-2020 shutdown, Chicisimo's tech endures via Fashion Taste API led by Gabriel Aldamiz-Echevarría, targeting retailers building taste infrastructure amid AI advancements in visual search and generative fashion tools.[2][5] Trends like edge AI for closets and AR try-ons will amplify its patents, potentially evolving influence through licensing or acquisitions—positioning it as foundational IP in a market where owning taste data defines winners, echoing its original consumer spark.
