Amsterdam-based VNYX has raised over €1 million to scale AI and robotics for automated fashion resale, reducing garment processing time from 19 minutes to 3 minutes per item. The company aims to achieve a “1-minute promise” and is deploying the VNYX100 system—capable of handling 100,000 items annually—by June 2026. Backed by strategic investors and government grants, VNYX is targeting the growing regulatory push in Europe on textile waste, especially under EPR rules. The startup is developing the VNYX1000 to process over 1 million items yearly. The technology is designed to transform fashion resale from a sustainability niche into scalable industrial logistics. The company is now seeking global partnerships for deployment in international fulfillment centers.
According to roboticsandautomationnews.com, Amsterdam-based startup VNYX has secured over €1 million in funding to scale its robotics and AI systems for automated fashion resale, aiming to reduce textile waste and streamline reverse logistics.
€1 Million Funding to Accelerate Resale Automation
VNYX raised more than €1 million in a mix of strategic investment and government grants, marking its transition into a post-revenue phase. The funding supports the expansion of its proprietary hardware and AI-driven software platform designed for garment processing. According to the report, the company has already achieved early commercial deployments with partners BOAS and Bever, processing up to 10,000 items annually. The financial backing includes non-dilutive support from the Netherlands Enterprise Agency and contributions from Stichting DOEN and Earthstar.
Hardware-Software Integration and Efficiency Gains
The VNYX10 system, currently in use, has reduced garment processing time from 19 minutes to approximately 3 minutes per item. The company aims to achieve a “1-minute promise” for resale processing, a benchmark it believes will make automated resale more efficient and profitable than traditional disposal methods. The integration of physical robotics with AI software is being developed in collaboration with engineering partner Spark Design & Innovation. Deeptech investors Baltic Business Angels and Squads Fund provided additional financial support.
Scaling to High-Throughput Systems
VNYX is preparing to roll out the next-generation VNYX100 system, capable of processing up to 100,000 items per year, with delivery scheduled for June 2026 to partner BOAS. The company is also developing the VNYX1000, an industrial-scale system designed to handle more than 1 million items annually. According to Romy Goedhart, co-founder, “Any brand who wants to go below one minute with us can join right now. We dump and burn one garbage truck of textile every three seconds, so every second counts. The right time to act is now.”
From Sustainability to Industrial-Grade Automation
VNYX positions its technology at the intersection of circular economy logistics and industrial automation. The company cites increasing regulatory pressure in Europe, particularly through extended producer responsibility (EPR) rules and bans on destroying unsold goods, as a key driver. Guus Balkema, CFO, said, “We have proven that fashion resale isn’t only the right thing to do for the planet, but it’s the right thing for your wallet too.” The company is now curating a shortlist of strategic VCs and global fashion brands for deploying the VNYX1000 in international fulfillment centers.
“Beyond the capital, our progress is driven by a world-class team and advisors whose dedication to stop fashion waste has turned a bold vision into reality in just 12 months.” — Vincent van der Holst, Co-founder and CEO
- €1 million funding raised (mix of investment and grants)
- Processing time reduced from 19 minutes to 3 minutes per garment
- Target: 1-minute processing time per item (1-minute promise)
- Current system (VNYX10) processes up to 10,000 items annually
- Next-gen VNYX100 system to process up to 100,000 items per year (June 2026 delivery)
Source: Robotics & Automation News
Compiled from international media by the SCI.AI editorial team.
