AI-Powered Vintage Curation

Your AI chineur never stops hunting

Trouvaille is an autonomous AI agent that scouts vintage fashion marketplaces around the clock, identifying undervalued designer pieces and curating collections you would never find on your own.

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Today's Finds — Curated by AI
Chanel Undervalued
Vintage tweed jacket, 1994 Autumn collection
€340 · Est. value €890
Maison Margiela
Tabi boots, white leather, size 38
€185 · Est. value €420
Hermès Rare
Silk scarf, Les Clés print, 1971
€95 · Est. value €280
How it works

Curation at scale, taste by design

01

Scout

The AI agent monitors Vinted, Vestiaire Collective, Depop, and niche European resale platforms 24 hours a day. It reads listings, analyzes photos, and cross-references pricing data.

02

Identify

Using pattern recognition trained on decades of fashion archives, Trouvaille spots undervalued pieces, rare colorways, and investment-grade vintage that human scrolling would miss.

03

Curate

Every find is organized into themed collections by era, designer, or style. Think a personal buyer from the Marché aux Puces, but working every marketplace simultaneously.

The world's fashion capital meets artificial intelligence

Paris is home to the greatest concentration of vintage luxury in the world. From the Marché aux Puces de Saint-Ouen to the curated boutiques of the 6th arrondissement, the city breathes fashion history. Trouvaille brings that Parisian eye for curation to the entire secondhand market.

$350B
Secondhand market by 2028
3x
Faster growth than new fashion
550K+
Instagram #curatedvintage posts
24/7
Autonomous scouting

The pieces that define wardrobes

Archive Runway
90s & 2000s designer
Investment Bags
Hermès · Chanel · Dior
Rare Accessories
Scarves · Jewelry · Belts
Hidden Gems
Undervalued · Mispriced

The best vintage finds were never meant to be found by accident

Trouvaille replaces luck with intelligence. An AI agent with Parisian taste, working every marketplace on earth, building collections that would take a human buyer months to assemble.

Browse Today's Finds