Fairly Made relies on AI to enhance sourcing transparency in fashion

For traceability, simply making declarations is no longer enough. Fairly Made, a French green tech company specialising in sustainable fashion, has unveiled a new tool, Supply Chain Intelligence, to help leaders in fashion meet regulatory requirements, such as the CSRD, ESPR or AGEC.

According to a survey conducted by the auditing firm PricewaterhouseCoopers (PwC), 47 percent of businesses cite data availability and management as major issues.

Fragmented data, a lack of internal skills and insufficient supplier engagement are key challenges. PwC suggests that Artificial Intelligence (AI) could be part of the solution by accelerating the speed of knowledge, decision-making and organisational change.

This is precisely what Fairly Made has invested in. Its "Supply Chain Intelligence" is a new module integrated into its SaaS platform, dedicated to traceability, environmental impact assessment, eco-design and product compliance.

Helping brands (and consumers) gain a clear and complete view of the supply chain

The aim of this AI is to help managers better manage their sourcing by making key data – certifications, energy consumption, partners, etc. – more easily accessible, thanks to a dynamic filter. The AI also provides structured analyses of this data.

Expected benefits include time savings and greater operational clarity. Fairly Made offers this solution as a SaaS subscription.

About CSRD, ESPR, AGEC

CSRD (Corporate Sustainability Reporting Directive) is a European directive that requires large companies to publish detailed reports on their sustainability (environmental, social and governance impact).

ESPR (Ecodesign for Sustainable Products Regulation) aims to make products placed on the European market more durable, repairable and recyclable.

AGEC (Anti-Gaspillage pour une Économie Circulaire) is a French law to reduce waste, improve sustainable production and promote recycling.

This article was translated to English using an AI tool.

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