Truss is a technology company that provides pricing intelligence and product identification tools for the second-hand fashion industry by leveraging artificial intelligence and market data. The platform lets sellers, boutiques and resale marketplaces determine the market value of items such as handbags, sneakers and apparel using real sales information rather than relying on listings or unverified estimates. Built on a database of more than a billion resale data points, Truss speeds up cataloguing and pricing while reducing guesswork for businesses and individual sellers.

Founded by graduates of the University of Warwick and headquartered in London, the startup has raised investment that includes support from FIGR Ventures and a grant from Innovate UK that Truss can use to improve product recognition algorithms and expand its data catalog. The company’s technology uses machine learning and image recognition to identify fashion items from a single photo and generate detailed product information and pricing recommendations based on verified historical sales across dozens of resale platforms.

Real Data for Real Prices

Manual pricing has long been a bottleneck for resale sellers, requiring research across multiple sites to find comparable sales, adjust for condition and then decide what a product might sell for. Truss replaces this process with automated valuation tools that draw on real sales history from more than 25 vendors. This allows users to understand current market value, seasonal trends and geographic differences in pricing that influence how quickly items sell and what they are worth.

The platform considers not only what an item last sold for but also factors such as how recently it sold, the reliability of the selling platform and specific attributes like colour, size and condition. These factors feed into a weighted valuation model that reflects real market behaviour instead of relying on subjective estimates. Sellers and platforms can use this information to price items more accurately, which helps reduce both under-pricing that cuts into profit and overpricing that deters buyers.

To support larger inventories, Truss offers batch pricing tools and an API that lets businesses upload thousands of stock keeping units at once, which returns valuations and product data in bulk. This capability helps marketplace operators and resellers maintain consistent pricing across large catalogues without the time and labour required for manual research.

AI-Driven Product Recognition

Truss goes beyond pricing with image recognition tools that identify garments and accessories from a single photo, returning details on brand, model, material and other attributes that feed into the valuation process. This helps remove barriers for sellers who might not know exact product names or specifications, especially for vintage or rare items.

The company has developed proprietary algorithms designed to deal with variations in product presentation, such as different lighting, angles and backgrounds in photographs. These systems match photos to entries in Truss’s extensive database so that sellers and resale platforms can retrieve accurate product descriptions and pricing recommendations faster than by manual search alone.

Product recognition and automated cataloguing reduce the time spent per item from minutes to seconds, which helps businesses process inventory more quickly and maintain throughput even when listing thousands of pieces. This efficiency can be particularly valuable during periods of high volume, such as seasonal sell-ins or when resellers acquire large consignments at once.

Supporting the Circular Fashion Economy

Second-hand fashion has grown as consumers seek more sustainable and cost-effective ways to shop, and resale marketplaces now play an important role in the broader fashion ecosystem. Truss contributes to this circular economy by making it easier for sellers to list items with accurate values and detailed descriptions, which in turn helps buyers find products with confidence.

By providing technology that accelerates cataloguing and pricing, Truss helps resale businesses operate more efficiently and reduce waste that comes from mispriced or stagnant inventory. Sellers can spend less time researching values and more time focusing on sourcing or customer service, while marketplace platforms can offer better searchability and more reliable price signals for buyers.

Large resale platforms, vintage boutiques and independent sellers all benefit from access to market data that once required hours of manual analysis to assemble. This access supports businesses of varying sizes and scales, from individual sellers checking a handful of products to enterprise operators managing extensive catalogues across regions.

Scaling With Investment and Partnerships

Truss has attracted funding and strategic backing that enable the company to expand its product offerings and data infrastructure, including broader coverage of everyday apparel and sneakers. A recent investment from FIGR Ventures unlocked match funding that activated an Innovate UK grant, supporting collaboration with partners such as Depop, Selfridges and the University of Warwick to build tailored algorithms and expand the database of identifiable fashion items.

These collaborations help Truss improve accuracy and broaden the range of products it can recognise and price, from high-end luxury goods to everyday apparel and sneakers. As the database grows, sellers gain access to more comparable sales history and richer product metadata that underpins pricing recommendations and product information.

Partnerships also create opportunities for resale platforms to integrate Truss’s technology into their workflows, which can support enhanced search functionality and better user experience for buyers and sellers alike. With investment and technical partnerships, Truss continues to build infrastructure that serves resale marketplaces, fashion retailers and data partners across regions.

Access to scalable pricing and recognition tools supports wider participation in the second-hand fashion economy by lowering barriers to entry for smaller sellers and helping established platforms optimise inventory management. By making pricing and product identification faster and more reliable, Truss helps the resale ecosystem operate more efficiently and serve consumers with up-to-date information.

As technology evolves and data sources expand, platforms like Truss may play a central role in shaping how fashion resale operates, supporting a system where accurate data and efficient pricing practices help to extend the lifecycle of garments and accessories while improving transparency for buyers and sellers.

Felix Jackson, COO, Truss