Fashion buying and inventory management platform Predictsys is harnessing Artificial Intelligence (AI) to predict fashion trends designed to help companies match supply with demand, while addressing the industry’s global waste problem.

The fashion industry is the second largest polluter in the world, just after the oil industry, and each year US$210bn worth of goods are either never sold or sold at less than the cost of production, according to Predictsys. This oversupply is partly due to supply-demand mismatch driven by inaccurate forecasts and manual buying, and inventory management processes.

Traditional fashion buying/ordering is driven by planners and buyers using historical data to determine which styles to buy/make and how much to buy/make. This leads to low accuracy and oversupply. Predictsys, however, uses advanced technologies such as AI, big data and customer sentiment analysis to improve fashion forecasting and generate SKU level forecasts with over 90% accuracy.

Predictsys also uses AI to automatically convert these forecasts into actionable planning, buying and inventory management recommendations.

“The fashion industry is under pressure to reduce its environmental impact while also increasing profitability,” says Abhinav Chandra, founder and CEO of Predictsys. “Our platform allows them to achieve both. We don’t simply give clients data which leads to analysis-paralysis but use the data to generate insights and recommendations which clients can directly act on. Our platform not only has the potential to change the future of the fashion industry but also the future of our planet.”

Using data from over 100 sources that influence future fashion trends, Predictsys generates automated, specific, and actionable recommendations for buying and inventory management that improves profitability and customer experience.

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The platform is designed to save time for planners, buyers and inventory managers while at the same time reduces waste and the negative impact on the environment.

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