This is a bet on repairs becoming infrastructure, not a niche, as regulators and brands push consumers from replacement to maintenance.
Lithuania-based Tingit has raised EUR 1.5 million in funding, backed by Coinvest Capital, Firstpick, NGL Ventures, Heartfelt, BADideas and Purpose Tech. The company runs a platform that connects consumers with repair service providers for clothing and other items, positioning itself as a “zero-effort repairs marketplace” designed to make fixing items as frictionless as buying new ones.
What Tingit is building
Tingit’s model is straightforward: users upload videos or photos of a damaged item, receive quotes from repair providers and then book, pay and arrange shipping through the platform. The company says repairs are typically completed in 7-10 days.
Operationally, Tingit is still early but shows initial traction. It has completed over 600-650 repairs and processed 2,500+ requests, with an initial focus on fashion-related repairs. Shoes account for around 70% of orders, a useful signal of where demand is most immediate and where refurbishment economics are easiest to standardise.
Why this round matters
The funding round lands into a market where the direction of travel is clear: repairing is moving from “nice-to-have” sustainability messaging to a regulated and brand-supported consumer behaviour.
Two forces are converging:
- Waste pressure is structural. The EU generates 12.6 million tonnes of textile waste annually, and only about 1% is recycled into new items. Platforms that extend product life have a credible policy tailwind.
- Brands are legitimising repairs. Fashion groups including Zara and Uniqlo have introduced repair services, signalling that after-sales care is becoming part of the core customer proposition rather than a boutique add-on.
Tingit’s pitch is to aggregate fragmented repair capacity into one consumer interface, then use software and data to reduce the cost and uncertainty that typically stop people repairing.
The strategic angle: AI as the margin lever
Tingit plans to integrate AI to automate damage analysis, apparel valuation, fashion authentication and product lifecycle tracking. If executed well, this is more than a product feature. It is the main path to making a repair marketplace scalable across categories and geographies.
In repair, the hardest problem is not demand. It is standardisation: accurately diagnosing damage, pricing consistently and routing jobs to the right provider while managing customer expectations. AI-assisted triage could compress that workflow, reduce manual handling and improve quote accuracy, which in turn improves conversion and repeat usage.
The company says the fresh capital will be used to scale its AI-powered platform across Europe, with expansion ambitions spanning fashion and electronics.
Team and execution reality
Tingit is led by co-founder Indrė Viltrakytė, who brings 15 years in the fashion industry and frames the company as a response to overproduction and overconsumption. The founders have also previously collaborated with leaders of Vinted, one of Europe’s best-known secondhand fashion marketplaces, giving the team relevant exposure to circular-economy consumer behaviour and marketplace mechanics.
The broader team includes CTO Tadas Maslauskas and Head of Service Providers Laimis Lomonosovas, roles that matter in a two-sided marketplace where provider onboarding and quality control often decide whether growth compounds or stalls.
The key execution risks are typical for the category:
- Service quality and consistency. Marketplaces live or die on repeat usage, and repairs are high-trust transactions.
- Unit economics across borders. Shipping, turnaround times and provider density will determine whether expansion works beyond a home market.
- Category stretch. Moving from fashion (where repairs are often straightforward) into electronics raises complexity in diagnostics, parts and warranties.
Still, with EU policy leaning toward repairability and consumer-facing brands normalising repair services, Tingit is targeting a market that increasingly looks like a new default. The challenge now is turning early traction into a repeatable, cross-border operating system for repairs.