OTTAWA, ONTARIO -- Kinaxis® Inc. (TSX: KXS), a global leader in supply chain orchestration, announced a new milestone in advancing large-scale supply chain optimization within the Kinaxis Maestro™ platform. Maestro already delivers high-performance optimization across complex global supply chains, and Kinaxis is now extending that leadership by leveraging GPU acceleration powered by NVIDIA cuOpt™ and NVIDIA AI infrastructure.

As supply chains grow in scale and complexity, planning models must reconcile tens of millions of variables across extended time horizons and multiple planning levels. As model size expands, the number of potential decisions can scale into billions, dramatically increasing computational needs. Organizations are no longer constrained by insight alone. They are constrained by how quickly they can iterate.

In testing on a large-scale semiconductor planning model with nearly 50 million decision variables, Kinaxis achieved up to a 12X reduction in total end-to-end calculation time. The model covered more than 40,000 SKUs across a six-quarter daily planning horizon. Planning cycles have been shortened from more than three hours to approximately 17 minutes. Core optimization solve time improved 23X, reducing compute time by more than 95% and shifting runtimes from hours to minutes, while maintaining comparable solution quality.

This shift enables organizations to move from long-running batch processes to interactive scenario iteration, reinforcing Kinaxis’ concurrent supply chain orchestration approach and allowing planners to evaluate more alternatives within operational decision windows.

“This milestone demonstrates how accelerated computing can change the way large-scale planning problems are solved,” said Gelu Ticala, Chief Technology Officer at Kinaxis. “When optimization shifts from hours to minutes, organizations gain the ability to iterate more frequently and evaluate more alternatives. That iterative speed is essential to enabling concurrent supply chain orchestration and advancing our agent-driven strategy.”

Kinaxis supports more than 400 global enterprises, orchestrating supply chain decisions across more than $200 billion in inventory across our customer base and generating more than 250,000 scenarios each month. At this scale, optimization performance directly influences decision latency and shapes how quickly organizations can respond to production constraints and shifts in demand.

Accelerated optimization also supports Kinaxis’ broader agent-driven orchestration strategy. Agent-based workflows rely on rapid scenario iteration and trigger multiple optimization runs as they evaluate alternatives. By reducing solve times, GPU acceleration expands the number of scenarios agents can assess within practical decision windows, strengthening the foundation for more responsive and adaptive supply chain decisions.

Key advancements include:

·Up to 12X faster solve times for a semiconductor wafer planning use case
·GPU-accelerated optimization using NVIDIA cuOpt
·Execution on NVIDIA AI infrastructure to support large-scale industrial models
·Integrated within the Maestro platform, connecting data, people, and decisions across the global supply chain

“The increasing complexity of global supply chains demands a fundamental shift to accelerated decision-making,” said Alex Fender, Director of Decision Intelligence at NVIDIA. “By integrating NVIDIA cuOpt into its Maestro platform, Kinaxis is empowering customers to achieve planning agility and scenario iteration to help navigate rapid change.”

Kinaxis will co-present these advancements during a session at NVIDIA GTC 2026.