Ex-Mango executives' fashion AI start-up Artiso raises €3 million

Artiso, a Barcelona start-up founded by former executives of the Spanish fashion retailer Mango, has raised more than €3 million in a pre-seed round to build what it calls an AI operating system for fashion design teams, according to an announcement dated October 28, 2026. The all-equity round was led by Criteria Venture Tech, with Swanlaab Venture Factory, Bynd Venture Capital and angel investors including Nicolaj Reffstrup, former chief executive of the Danish label GANNI, also taking part.

Behind every garment in a shop is a long chain of creative and technical work. Designers gather inspiration into mood boards, turn ideas into sketches and computer-aided designs, choose prints and colours, and then produce a "tech pack", the detailed instruction sheet that tells a factory exactly how to make the piece: measurements, fabrics, trims and stitching. In many fashion companies these steps still run across separate tools, spreadsheets and email threads, and moving a design from idea to factory can take months.

Artiso's pitch is to put that whole chain on one platform and use artificial intelligence to speed up the repetitive parts. Its software is described as using "agentic" AI, systems that can carry out a series of tasks rather than answer a single question, to help create mood boards, develop designs and generate prints. The company says the tool is built on each brand's own data, so that what it produces follows that brand's style and past collections rather than a generic look. These are the company's descriptions of its product; independent results from customers have not been published.

The founders' background is the main reason the round has drawn attention. The three founders held executive roles at Mango and bring direct experience of how a big design and buying team works. The backing of Nicolaj Reffstrup, who led GANNI, also signals interest from people who have run fashion brands, not only from technology investors.

For India's fashion industry, the story points to a change that could reach its designers and export houses too. Garment makers that produce for international brands work from those brands' tech packs and samples. If brands adopt AI tools that generate designs and technical files faster, suppliers will be expected to respond faster, and Indian design teams may adopt similar tools for their own labels. The question for workers is whether these tools take over routine tasks and leave more time for design, or reduce the number of design jobs; the company presents its product as support for creative teams.

Short-term: Artiso will use the money to build its product and team and to support roll-outs at larger fashion companies. Brands testing the tool will judge it on whether it shortens the time from first idea to a factory-ready design.

Long-term: If tools like this become standard, the early stages of fashion design could change in the way that design software changed drawing boards: faster sampling and fewer rounds of revisions, but also new skills that designers will need, such as working with and checking AI output.

Who is affected: Fashion designers, product developers and technical designers; brands and retailers planning collections; garment makers and exporters, including those in India, who work from brands' tech packs; and investors watching AI tools for creative industries.

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