Try on lingerie virtually; every pick has an AI judgment receipt. Fit Receipt is a reference implementation. The agent handles chat; code protects facts and pricing. JEV (TypeSafe) is a judgment model that scores trade-offs with calibrated confidence in ~300ms—not essays. Low-confidence results stay unresolved; judgments are recorded; works without JEV. Photos stay in your browser; no server photo storage. JEV sees typed fields, never the photo. Rate-limited API. Vercel + open source.
Oh, the fact that the photos never get uploaded to a server is a huge plus!
I would just love to try this out.
For me, it is always a juggle to find a bra that really fit well. To be able to try it virtually and in your own private space would for sure support.
Do you also get like help and support from an AI agent to find the best fit?
We're live! 🔥 Day 1 update: the Jev integration above is running in production right now — every judgment on the page carries a real receipt. I'll be in the comments all day: tell me where your agent gets unsure, and I'll tell you where ours hands off.
Hi Product Hunt! I'm Crystal, founder of NUDE, a Taiwanese intimate apparel brand.
To buy or not to buy — that is always the question for a shopaholic. 🛍️
After years in our fitting rooms, I've learned there is rarely a 100% "right" bra. Preference and habit matter, but so do things no algorithm sees: the mood in the room, the light, how the person helping you makes you feel. A good store follows a quiet order: you see the piece, we learn how you'll wear it, you try it on, and only then do we talk about the cost.
Fit Receipt brings that order online, along with the part of good service that's about honesty.
The agent understands the person. JEV, a judgment model, weighs the trade-offs between styles. Code protects the facts: product data, prices, promotions. The person owns the decision.
Every judgment leaves a receipt, uncertainty included. When the top option sits at 69%, it still says "trade-off still to confirm."
We don't cure choice paralysis. We show you when it's justified.
I'd love to know: where should AI explain its reasoning and where should it make room for irrational human shopping behavior?
About Fit Receipt on Product Hunt
“A private fitting agent that knows when to call JEV”
Fit Receipt launched on Product Hunt on September 25th, 2026 and earned 71 upvotes and 9 comments, placing #18 on the daily leaderboard. Try on lingerie virtually; every pick has an AI judgment receipt. Fit Receipt is a reference implementation. The agent handles chat; code protects facts and pricing. JEV (TypeSafe) is a judgment model that scores trade-offs with calibrated confidence in ~300ms—not essays. Low-confidence results stay unresolved; judgments are recorded; works without JEV. Photos stay in your browser; no server photo storage. JEV sees typed fields, never the photo. Rate-limited API. Vercel + open source.
Fit Receipt was featured in Productivity (661.5k followers), Fashion (14.6k followers), Developer Tools (520.1k followers) and Vercel Day (40 followers) on Product Hunt. Together, these topics include over 256.2k products, making this a competitive space to launch in.
Who hunted Fit Receipt?
Fit Receipt was hunted by Crystal Chang. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Fit Receipt stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Crystal Chang