Epytom
The first conversational AI fashion assistant.
| Date | Investors | Amount | Round |
|---|---|---|---|
| - | investor | €0.0 | round |
| investor investor | €0.0 | round | |
$1.0m | Early VC | ||
| Total Funding | 000k | ||
Epytom operates as a personalized fashion recommendation platform, initially launched as a chatbot-based service. The company was founded in 2015 by Anastasia Sartan and Maria Liberman and is headquartered in San Francisco. Sartan, who serves as CEO, previously founded Trends Brands, one of Russia's first e-tailers to leverage social media, an experience which provided her with a foundation in e-commerce and fashion. The idea for Epytom emerged from Sartan's desire to create an AI-based personal style assistant after her experiences in the fashion industry.
The business provides users with style recommendations and tutorials tailored to factors like weather, personal taste, and the user's existing wardrobe. Initially launched on Facebook Messenger, the service attracted 30,000 subscribers on its first day. Epytom functions as a stylist-bot, educating users on creating a perfect style and offering curated shopping suggestions. The core of the service is to help users build a capsule wardrobe of around 40 items to create numerous outfits, minimizing waste and simplifying fashion decisions. By collecting user feedback and data on preferences, Epytom uses neural networks to reverse-engineer a user's style profile.
Epytom's business model has evolved to include creating custom-made apparel designed by its proprietary AI. This AI-driven approach analyzes a garment's attributes to generate a production-ready pattern, a departure from models that simply generate images. This allows the company to offer a customer-centric alternative to fast fashion, where the user's data directly informs the design and production process. The company also created opportunities for brands by featuring their products in curated selections, associating them with the user's ideal style. While the company was reported as unfunded in one source, it received early backing from investors including the Founders Fund.
Keywords: fashion technology, AI stylist, personal styling, chatbot, capsule wardrobe, fashion recommendation, custom apparel, personalized fashion, wardrobe planning, e-commerce, style assistant, neural networks, machine learning, made-to-order clothing, fashion data, outfit recommendation, mindful consumption, digital stylist, conversational AI, style profile