Alta Daily, launched in 2025, is a fashion app that lets users photograph and digitize their entire wardrobe, then receive outfit recommendations through natural language prompts while viewing looks on a personal digital avatar (Meta AI Blog). At the core of the app is Meta's Segment Anything Model (SAM), which has been used to segment and digitize millions of outfits by removing backgrounds from user-uploaded images—a critical feature for the app's clean, magazine-style aesthetic (Meta AI Blog).
The fashion industry presents unique segmentation challenges: inconsistent lighting, reflective surfaces, jewelry details, and varied backgrounds—from white sneakers on white walls to blue sweaters on blue blankets. The Alta team tested multiple segmentation models across eight product categories and found that SAM consistently delivered the best results, handling everything from mirror selfies to floor-laid items (Meta AI Blog). Beyond performance gains, SAM has had significant financial impact; founder Jenny Wang noted that external segmentation APIs cost a few cents per image, which would add up quickly at scale. By using SAM, Alta has processed more than 20 million images without incurring exorbitant costs, allowing the company to focus on product quality rather than infrastructure expenses (Meta AI Blog).
For commerce practitioners, this case demonstrates how open-source AI models can enable consumer-facing styling experiences that increase wardrobe utilization—addressing the fact that most people wear only an estimated 20% of their closet (Meta AI Blog). The app has already gained a global following in the United States, France, Germany, Mexico, and the Netherlands, and the Alta team is experimenting with Meta's SAM 3D models to unlock even more immersive avatar interactions (Meta AI Blog).