eBay and Google Back Whering's Digital Wardrobe Platform
Whering, a UK-based digital wardrobe app, has raised $7m in seed funding led by eBay Ventures and Google's AI Futures Fund. Founded in 2021 by Bianca Rangecroft, the platform lets users photograph and catalogue the clothes they already own, then plan outfits, pack for trips and share styling ideas - positioning itself around getting more out of an existing wardrobe rather than buying new.
The company says it has passed 10 million users globally, though the figure is self-reported and it has disclosed neither engagement nor revenue. The new capital is tied to features developed through the Google fund: planned additions include recommendations that factor in weather, mood and occasion, gallery scanning that identifies garments from a user's camera roll, image enhancement and virtual try-on. Whering also intends to deepen its resale integrations, pulling wardrobe management, styling and second-hand selling into a single platform.
Why it matters: The sum is small, but the cap table is the story. eBay Ventures also joined Fleek's larger round, covered elsewhere in this issue, and demonstrates that eBay is taking positions across the resale stack, from the sorting-and-grading infrastructure that supplies second-hand stock to the consumer app that could originate it. Google's AI Futures Fund adds a further perspective - that a digitised wardrobe, understood item by item, becomes a useful surface for personalised, eventually agent-led commerce.
The catch is the one every closet app eventually meets: cataloguing what people own is a data-collection exercise, and ten million users only matters if the resale loop turns that data into transactions. For an industry still short of circularity models that hold up commercially rather than rhetorically, whether Whering can convert wardrobes into a marketplace is the test that counts.
Fleek Raises $25m to Build AI Infrastructure for Secondhand Fashion
Fleek, a B2B marketplace and software company for the global secondhand clothing trade, has raised $25m (£18.7m) in Series B funding to digitise a supply chain it describes as manual, fragmented and largely offline. The round was led by Burda Principal Investments, an early backer of Vinted, with participation from eBay, FJ Labs and H14 alongside existing investors Andreessen Horowitz, HV Capital and Y Combinator.
At the centre of the business is Fleek Sort, a custom vision-language model trained on millions of resale transactions gathered across Fleek's network over the past four years. The model works from photographs or videos to identify, categorise, grade and merchandise used garments - the labour-intensive step that has historically happened by hand in sorting hubs. It is already in use by graders in Pakistan, India and Dubai, with pilots running in the UK, Europe and the US, and processed stock is listed automatically on Fleek's marketplace, where AI handles pricing, search and buyer matching. Fleek puts the scale of the opportunity at up to 24 billion items moving from donation bins to sorting centres each year, and says resale demand is growing three times faster than the wider apparel market, though both figures are the company's own.
Kirstie Pickering
Why it matters: Most resale coverage fixates on the shopfront - the apps and consumer marketplaces - while the actual constraint sits upstream, in the warehouses in Karachi and Dubai where clothing is graded by hand before it can be sold. Fleek is betting on the unglamorous middle, and the composition of the round tells you others are too: eBay's strategic involvement and Burda's Vinted pedigree suggest resale infrastructure is now being treated as a category worth owning, not just a feature.
The open question is accuracy. Grading condition, authenticity and value from a photo is exactly where vision models tend to be brittle, and a model that misgrades at scale creates returns and disputes rather than efficiency - so the four-year training set is the claim to watch, not the funding total. For an industry under growing pressure to prove its circularity credentials are more than marketing, whoever makes secondhand sorting genuinely scalable holds real leverage.
Ex-Amazon Chief's Auger Targets Fashion's Supply Chain With $50m Round
Auger, a Bellevue-based supply-chain software company founded by former Amazon operations chief Dave Clark, has raised $50m in Series B funding led by Eclipse, with existing backer Oak HC/FT following on. The round takes total funding to $150m for the two-year-old company, which sells software that sits on top of a business's existing ERP, warehouse and demand-planning systems, unifies the data, and uses AI agents alongside conventional optimisation to make and carry out operational decisions rather than simply flagging them for a human.
Dave Clark, who spent 23 years at Amazon running its worldwide operations and later its consumer business, describes the product not as a tool but as "the new employee," and says that at sports-merchandise customer Fanatics roughly 85% of the decisions in the process Auger manages are now made autonomously, a figure the company has not independently substantiated. Auger has built a dedicated fashion and beauty division, led by co-founder Leigh Anne Clark, on the premise that apparel runs one of the most wasteful supply chains outside groceries. Its named customers so far span Meta's virtual and augmented reality unit, Fanatics and Kimberly-Clark, with a further eight to ten in pilots or contract talks. The company has not disclosed revenue, and Clark has set out the deliberately outsized ambition of routing half of US GDP through the platform by 2030.
Why it matters: The number to watch is not the $50m but the claim underneath it that AI can move from generating insight to making and executing operational decisions on its own. Fashion is an obvious proving ground, since apparel planning, allocation and inventory remain heavily manual and produce some of the industry's worst overproduction and markdown waste - the exact costs an autonomous layer is meant to strip out.
Clark's bet is also a pointed one. He raised for precisely the kind of specialised enterprise software that general-purpose models are supposed to make redundant, arguing that messy operational domains reward deep, domain-specific systems over frontier models. Whether that holds is unproven here. Set against Fleek and Whering elsewhere in this issue, it's clear that capital is now flowing into AI at every layer of the fashion chain, from the sorting floor to the wardrobe to the planning systems that decide what gets made in the first place.