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Cloud machine learning platform for retail demand forecasting and planning.
Generates granular demand forecasts using self-learning machine learning models. Optimizes merchandise financial planning and multi-channel assortment strategies. Automates inventory allocation and markdown timing to maximize gross margins. Provides network flow optimization across complex retail supply chain networks.
Replaces legacy time-series forecasting with continuous self-learning algorithms. Leverages cloud-native supercomputer processing to analyze high-volume retail transactions. Integrates prescriptive analytics to recommend immediate pricing and allocation decisions. Provides modular scalability across assortment, inventory, and network planning functions.
Category: AI & Automation
Team Size: 100+
Visit WebsitePredictix is a cloud-native predictive and prescriptive analytics SaaS platform designed for retail enterprises. The platform utilizes high-performance computing and machine learning algorithms to model complex retail demand patterns. It provides end-to-end capabilities across merchandise financial planning, assortment planning, category management, and network flow optimization. In 2016, Predictix was acquired by Infor to power its CloudSuite Retail platform.
Predictix was founded in 2005 by Molham Aref in Atlanta, Georgia. Aref recognized that legacy time-series demand forecasting methods could not handle the complexity and data volume of modern omni-channel retail environments. The team developed a cloud-native platform leveraging machine learning to deliver high-scale predictive analytics, ultimately leading to its acquisition by Infor in 2016.