Fit Receipt

A private fitting agent that knows when to call JEV

Vercel DayDeveloper ToolsProductivityFashion

▲ 69 votes9 commentsLaunched Sep 25, 2026

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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.

AI Analysis

📝 Summary

Fit Receipt offers a private AI fitting agent for virtual lingerie try-ons, generating an 'AI judgment receipt' for each selection. The core technology is JEV, a TypeSafe judgment model that evaluates trade-offs with calibrated confidence in approximately 300ms. It features a chat-handling agent, fact and pricing protection in code, and operates without server-side photo storage—all processing stays in the user's browser. JEV only accesses typed fields, not images. It's an open-source reference implementation hosted on Vercel, serving as a developer tool. It addresses key pain points like privacy risks in sharing intimate photos and slow or uncalibrated AI advice in online fashion. The value proposition is a trustworthy, private, and efficient virtual fitting experience with transparent AI judgments.

📈 Market Timing

In 2025-2026, AI multimodal and judgment models are reaching practical maturity, aligning with rising consumer demand for personalized, privacy-first online shopping in fashion and intimate apparel. Post-privacy regulation trends and browser-based AI capabilities support this approach. Virtual try-on interest is growing amid e-commerce expansion. Excellent Timing.

✅ Feasibility

High. The reference implementation on Vercel with browser-only photo processing minimizes storage/compliance risks and operational costs. Technical complexity is reduced via JEV integration and open-source code; it works without the model. Strong scalability with rate limits, though AI accuracy in fashion judgments remains a validation need. Low supply chain risks as a digital tool.

🎯 Target Market

Primary segments: privacy-conscious women aged 18-40 shopping for lingerie online (mainly US/Europe) and developers/AI enthusiasts interested in fashion-tech reference implementations and judgment models. Core pain points include fit uncertainty without trying on and privacy fears with photo uploads. Virtual fashion AI market shows strong growth and demand; users likely willing to pay for reliable private tools.

⚔️ Competition

Medium. Direct competitors: 1. Wanna (wanna.co), 2. Virtusize (virtusize.com), 3. True Fit (truefit.com), 4. Perfect Corp YouCam (perfectcorp.com). Advantages: unmatched browser-only privacy (JEV never sees photos), fast calibrated judgments vs long responses, open-source reference impl. Disadvantages: niche to lingerie, functions as tech demo/reference rather than full consumer app, potential limits in visual realism compared to image-generating competitors.

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