FitLedger

FitLedger is a mobile + web app (AI + traditional) that helps shoppers buy the right size across brands by building a private “fit ledger” from what they already own. Users add items by scanning a barcode/receipt, forwarding order emails, or searching a product catalog; then they rate fit on a simple scale (tight/true/loose) for key areas (waist, rise, chest, shoulders, length). The app learns a user’s body-and-preference profile and maps it to brand-specific sizing quirks using aggregated, anonymized fit feedback from other users. Instead of promising perfect body measurements (often inaccurate), FitLedger focuses on practical outcomes: “In Brand X, size 31 fits like your Brand Y size 32.” It also flags high-risk purchases (“this fabric has low stretch; your past returns suggest sizing up”) and suggests alternative sizes before checkout. Monetization is realistic: affiliate revenue from partner retailers plus a small subscription for power users (wardrobe tracking, multi-profile household, and advanced fit insights). The hard part is data density; the MVP should start with a few high-volume categories (jeans, tees, sneakers) and a limited set of brands to avoid a thin, unreliable experience.