SYDNEY, March 11, 2026 /PRNewswire/ — Manhattan Associates Inc. (NASDAQ: MANH) today announced that Rainforest Distribution Corp., a full-service food and beverage distributor, has selected Manhattan Active® Supply Chain Planning (SCP) to unify its supply chain functions, transform its end-to-end planning processes, drive higher service levels, and support continued growth. This will result in greater agility enabled by unified planning, enhanced forecasting accuracy powered by AI-driven insights, and seamless alignment between planning and execution systems.
Rainforest Distribution chose Manhattan Active Supply Chain Planning to modernise its demand planning, forecasting, and replenishment processes, all on a single unified, cloud-native platform. By moving away from fragmented legacy tools to a single planning solution, Rainforest will gain real-time visibility and continuously balance service levels, cost, and capacity across its network, while responding faster to changing customer demand.
"As our business continues to scale, the complexity of our supply chain has increased exponentially," said Alexander Ridings, CEO, Rainforest Distribution. "We needed a modern planning solution that could keep pace with that growth, give our teams a single, trusted view of demand and inventory, and help us serve customers with greater reliability. Manhattan Active Supply Chain Planning gives us the unified, intelligent platform we were looking for to align our planners, our operations, and our strategic growth ambitions."
"Rainforest Distribution operates in an environment where agility, accuracy, and responsiveness are critical," said Stewart Gantt, executive vice president of Global Services, Manhattan Associates. "We are excited to partner with them on this transformation to help them unlock new levels of efficiency and build a more resilient, data-driven supply chain."
Manhattan Active Supply Chain Planning aligns planning and execution around a shared strategy, helping organisations eliminate systemic and operational silos and drive coordinated, enterprise-wide decision-making. Built on Manhattan’s cloud-native, microservices-based Manhattan Active® Platform, the solution is engineered to adapt in real time to shifts in demand, labor, orders, and capacity, aligning planning functions with execution across distribution and transportation operations.
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ABOUT MANHATTAN ASSOCIATES
Manhattan Associates is a global technology leader, providing supply chain and omnichannel commerce solutions with unmatched AI capabilities. We design, build and offer best-in-class, AI-powered, cloud-based solutions that drive resilience and efficiency for businesses. We enable enterprises to uniquely unify front-end sales with back-end supply chain execution.
Our commitment to innovation, cloud-native platform and API-first architecture create simpler experiences and faster paths to value for our customers. We empower them to preempt and react to emerging trends and global disruptions with technical expertise and operational confidence, transforming challenges into competitive advantage. For more information, please visit www.manh.com.
ABOUT RAINFOREST DISTRIBUTION
Rainforest Distribution Corp. is a full-service food and beverage distribution company operating a network of distribution centers across the eastern United States with refrigerated, frozen, and ambient fulfillment capabilities. Purpose-built as a platform for incubating, supporting, and scaling emerging and high-growth brands, Rainforest gives manufacturers a clear path from regional launch to national reach.
For retailers where differentiated assortment is critical to driving traffic and loyalty, Rainforest delivers a curated, trend-forward product mix that makes store sets more compelling. Combined with deep supplier partnerships, enterprise-grade food safety standards, and investment in advanced supply chain technology, Rainforest serves as a value-added partner to national chains, regional grocers, and independent operators alike. For more information, visit www.rainforestdistribution.com.
