Fetched about 2 hours ago
Monday, July 6, 2026
to Monday, August 17, 2026
•
1 month long
Event Type
online
25
Participants
$6,000
Prize Pool
2
Est. Projects
Builders, developers, and visionaries: it’s time to design solutions that redefine the next generation of consumer experiences. The YouCam API Skin AI & Apparel VTO Hackathon is your launchpad. We’re opening our most advanced, field-tested AI/AR infrastructure so you can move beyond the sandbox and build real products, including agentic AI workflows.
We want you to push innovation to its limits by integrating YouCam APIs into your big idea, whether it’s a self-learning styling AI agent, a personalized skin diagnostic tool, or a solution to real user problems. Bring your boldest architectural concepts—and we’ll back them with serious prize money.

All solutions must integrate at least one YouCam API and demonstrate clear consumer or retail value. Your solution needs to clearly align with whichever topic you choose, both in how it's built and how it's described.
Pick the topic that best fits your project and submit:
People don't wonder about their skin in the abstract, they wonder right before a purchase, right after a bad breakout, right when they're standing in front of a mirror deciding whether something is working. Build something that meets that moment. Use YouCam's Skin AI, alone or combined with other YouCam APIs, to help someone understand their skin and know what to do next.
Most online shopping decisions still come down to a guess, will this fit, will this look right, is it worth the return shipping. Build something that replaces that guess with something closer to certainty. Use YouCam's generative Apparel VTO, alone or paired with other YouCam APIs, to help someone make a buying decision with more confidence.
Beauty and fashion decisions rarely happen in isolation, what someone wears and how their skin looks are part of the same self-image. Build something that brings Skin AI and Apparel VTO together into one experience, rather than treating them as two separate features. We want to see what's possible when both capabilities work as one.