True Fit

True Fit is an enterprise fit and sizing intelligence platform for apparel and footwear retailers. It recommends sizes from real purchase and return data, adds virtual try-on, and can plug into existing AI agents through MCP.

True Fit is a fit and sizing intelligence platform built for apparel and footwear retail. It draws on roughly 20 years of real purchase and return outcomes to tell a shopper which size will actually work, rather than relying on a static size chart. Retailers deploy it in one of two ways: a ready-made shopping agent with native virtual try-on, or a fit layer exposed through MCP that feeds sizing context into an AI stack the retailer already runs. The core mechanism is a shopper profile matched against product data. A shopper enters their usual size and reference garments, and True Fit compares those details with item measurements and cross-brand fit behavior to recommend a size and explain how the piece will feel. Guidance appears on product pages, listing pages, search results and the homepage, and the conversational layer lets shoppers ask about fabric, reviews and how a specific size will sit. Virtual try-on extends this by styling a selected item on the shopper's own photo (or a saved one), so the shopper can see the look and receive sizing guidance alongside it. True Fit is aimed at retail teams rather than individual consumers: apparel and footwear merchandisers, ecommerce and conversion leads, and support managers tired of repeated sizing questions. It also covers verticals such as kids, performance, intimates, uniforms, staff and workwear, and campus or school spirit stores. For retailers that already run an assistant, the MCP route adds fit intelligence without replacing their interface. The tradeoffs are structural. True Fit is an enterprise integration, so value depends on catalog data quality and merchant setup effort, and the homepage does not publish pricing or a self-serve signup, so buyers must go through a demo request. It is also narrowly focused on fit and sizing within apparel and footwear, which means it will not serve categories outside that scope. Competitors in virtual try-on and sizing are numerous, so the differentiation rests on the depth of historical outcome data, which is hard to verify from the outside.