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Just an hour’s drive from their native Auvergne, Nadia Beaune and Maxime Gros started their domaine Les Rêves Oubliés — "the Forgotten Dreams" — in 2018 in the small village of Maure in the Forez region. Hidden behind the western slopes of the Massif Central, the Forez benefits from cold and dry winters, warm summers, and high altitude. Their cellar sits at 650 meters elevation in the heights of Marcilly-le-Châtel, with vines spread across about ten parcels on hillsides between 350 and 500 meters on granitic, basaltic and volcanic soils. The combination imparts a particular volcanic ashy aromatic to the local Gamay variety: Gamay Saint Romain Noir à Jus Blanc. Nadia had nothing predestining her to wine — she worked in the hospital sector before training under Christian Ducroux in Beaujolais, a biodynamics and horse-work advocate. She and Maxime also worked with François Dhumes, Michel Guignier, and Catherine Dumora before launching their own domaine. The wines are very much like Nadia: deeply emotional, powerful, complex, nurturing and sometimes on the edge of what is considered to be consensual.
From soil to table
Approach
Nadia and Maxime produce vins authentiques, au plus proche de la nature — authentic wines, as close to nature as possible. They have chosen to remain human-scale to understand each parcel’s specific needs. All work is done by hand and with horse-drawn traction. No inputs, no SO2, no fining, no filtration. Indigenous yeasts only. Grapes are harvested manually with sorting done in the vineyard. Natural deposits in bottles are accepted as markers of authenticity. They are expanding biodiversity on the domaine by planting fruit trees and small fruits alongside the vines, and have introduced hybrid grape varieties (Seibel 54-55, Souvignier Gris) as part of their commitment to resilient, chemical-free viticulture.
Portfolio
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Les Rêves Oubliés’s presence in the graph: its wines, the venues that carry them, and its US importer. Where a link isn’t resolved yet, it shows as a dashed placeholder (the shape of the model, ahead of the data).
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