Agentic Styling and Shopping: Why We’re Backing Alta

I’m someone who wears all black to work most days because it’s the easiest, and I’m not alone. People have long struggled with what to buy and wear—whether it be for work, play, special occasions, and everything in between. Only about 20% of clothes in a closet get worn regularly; for me, it’s probably closer to 10%. 

Historically, solutions for this have included personal shoppers and stylists, but these are out of reach for most people and offer one-time fixes. First-gen personalized shopping experiences included companies like StitchFix, but now, for the first time, generative AI models can break down and personalize style at the truly individual level to disrupt the $20B affiliate marketing industry and $160B U.S. online apparel market.

Introducing Alta. At Menlo Ventures, we were looking for a fashion-forward founder that embodied a few things: had a deep technical understanding of how models can decode fashion, had a background in retail/fashion, and natively understood how to leverage today’s social networks for a distribution advantage. We found that in Alta founder and CEO Jenny Wang.

Today, we’re thrilled to announce that we’re leading Alta’s $11 million seed round, investing alongside Aglaé Ventures (an investment firm backed by the Arnault family of LVMH), Benchstrength Ventures, and others. 

Solving Personalized Shopping

When I shop online for something like a white tee, I typically start with a Google search, like most people do. But those search results aren’t tailored to my personal style or preferences. I often get options ranging from men’s to women’s sizing in brands from Shein to Tom Ford. In order to truly solve personalized shopping recommendations, a product needs to know two things: what you already own, and what will look good on you. 

Getting started with Alta is easy. First, upload your closet, which can be done a number of ways: from your photo library, email receipts, camera capture, and soon, voice and video input. Outfits begin to generate in moments; an optional style survey helps provide additional detail. Alta learns continuously, with recommendations becoming more personalized as you upload additional items from your closet. This helps Alta learn about your style preferences, favorite brands, and budget constraints.

Decoding Fashion

Style-conscious consumers will only keep using Alta if the outfits generated look good on them, which means Alta needs to know how to decode fashion—and well. But fashion is surprisingly complex; for example, there are over 250 shades of red alone, each requiring different considerations for pairing with 200+ shades of brown pants before considering texture and cut. Alta tackles this challenge using over a dozen specialized models, trained with stylists-in-the-loop reinforcement learning that provide ongoing tuning. This knowledge base becomes further personalized to each user by ingesting their direct feedback, such as,“Never give me denim on denim,” and other style preferences they input directly. Lastly, you can see how the outfit looks on you with Alta’s virtual try-on avatar.

Agentic Shopping

Alta launched two months ago, and people are now generating over 270,000 outfits a day on the app. The app provides users with daily outfit ideas and real-time styling advice for special events or occasions. Users have shared their Alta-generated outfits on social media for occasions ranging  from “Costco shopping run” to “I’m getting fired tomorrow, need to look confident meeting with my boss” to “I want to look hot at coffee with my ex.” Users view Alta as their trusted personal stylist. The next frontier is agentic shopping; Alta has partnered with over 4,000 brands to deliver shopping recommendations tailored to individual style and existing wardrobes.We’re thrilled to support Jenny Wang and the Alta team as they revolutionize personalized shopping. Want to unlock your wardrobe’s full potential? Check out the app now at https://www.altadaily.com/.