Vintage Moroccan Rug - 2'9" × 5'9"- TO6003

Vintage Moroccan Rug - 2'9" × 5'9"- TO6003

Brand: The Boho Lab
432.00 USD In stock Buy at Merchant

VINTAGE MOROCCAN RUG Rug Description This authentic vintage Moroccan rug is handwoven by Berber artisans and features a timeless composition of bold diamond medallions and traditional Amazigh symbols woven across a natural ivory wool field. Soft warm brown motifs create a beautiful contrast, highlighting the minimalist elegance and rich cultural heritage of Moroccan tribal weaving. The repeating diamond motifs are traditionally associated with protection, harmony, and the continuity of life, while the smaller symbolic figures represent prosperity, family, and personal stories passed down through generations of Berber artisans. Its balanced geometric design and naturally aged wool give the rug a warm, organic character that only authentic vintage pieces can offer. Hand-knotted from organic wool and naturally aged over decades, this one-of-a-kind vintage rug combines exceptional craftsmanship with timeless versatility. Its neutral palette and classic tribal design make it an effortless addition to organic modern, Scandinavian, Mediterranean, rustic, Japandi, minimalist, wabi-sabi, or traditional interiors. Rug Specifications Dimensions: 84 × 176 cm / 2'9" × 5'9" (approximately) Material: Organic Wool Pile: Medium Pile Made: Handmade in Morocco Disclaimer Subtle variations in weaving, asymmetry of the geometric motifs, irregular edges, and natural color variations are authentic characteristics of genuine handmade vintage Beni Ourain rugs. These unique details reflect their artisanal craftsmanship and make every piece truly one of a kind. Please Note This rug is shipped directly from Morocco. Delivery times may be longer than items available from our Montreal location. Import duties, customs fees, and local taxes may apply and are the responsibility of the buyer.

Variants (1)
  • Default Title — 432.00 USD — In stock

How AI sees this product

The more complete this product's details, the more confidently AI assistants can understand and recommend it.

80%