SAN FRANCISCO, Sept. 26, 2023 /PRNewswire/ -- Last week, Noodle.ai, the leader in Supply Chain A.I., had its patent application filed for the core GPP technology underlying its new Generative Supply Chain Planning. The technology, which is probabilistic in nature, has the ability to drive dramatic increases in supply chain profitability and dramatic decreases in supply chain waste.
"We are convinced the GPP technology will mark a key milestone in the transition to a future of Generative Planning." said Stephen Pratt, Founder & CEO of Noodle.ai. "This is a once in a generation breakthrough to make material improvements in global supply chain efficiency and waste reduction."
Why is Generative Planning Revolutionary?
Traditional planning solutions have struggled to keep pace with the complexities and uncertainties of modern global supply chains. The existing deterministic approaches usually lead to sub-optimal, and often infeasible, plans. These plans are created by decades old stagnating technologies which create an imbalance between supply and demand, lower profits, and huge amounts of waste because remedial actions are often required to satisfy demand.
"This technology further grows our competitive advantage over other supply chain alternatives," said Mahriah Alf, Noodle.ai Chief Product Officer. "Generative Planning builds on the Probabilistic System of Intelligence currently driving our products and is a quantum leap forward."
Noodle.ai Generative Planning optimizes entire supply chains simultaneously through Large Graph Models (LGM) that continually learn and improve.
Hyung-il Ahn, Noodle.ai, Chief AI Scientist, says "Noodle.ai's Generative Planning incorporates cutting-edge generative AI technologies?such as attention-based graph neural networks (GNN), offline deep reinforcement learning (Offline RL), and probabilistic policy simulations. This potent combination generates dynamic supply action plans that are both feasible and network-wide optimized and consider time-varying supply chain objectives and probabilistic factors like demand, lead time, and production variabilities."
Generative Planning Results
Noodle.ai Generative Planning has shown extraordinary promise when tested using historical data from a North America-based consumer goods company with a complex supply chain network. Generative Planning simultaneously increased revenue and decreased costs by reducing out of stocks and lost sales by 75% and reducing excess stock by 20% with a corresponding inventory holding cost impact.
A Generative AI Solution that adapts to your ever-changing Business Objectives
Generative Planning can adapt to different corporate objectives, whether they are maximizing profits, service levels, minimizing risk, cost containment, or other metrics. By employing generative policy models trained on real-world network transition data, Generative Planning performs probabilistic simulations to create optimal supply plans that are tailoring to your corporate objectives and resilient to the uncertainties of today's global supply chains.
Generative Planning data science and data flow development are complete, and the broader application is being productized to ensure it meets Noodle.ai high standards of availability, security, scalability, and ease of use. Noodle.ai Generative Planning will be available to initial customers in Q1 of 2024 with an initial focus on demand and finished-goods distribution.
Noodle.ai is currently a probabilistic system of intelligence that supercharges your current planning and transaction systems with the power of probabilities. Unlike traditional systems that rely on fixed rules and simplified assumptions, Noodle.ai uses cutting-edge AI/ML technology to conquer variability and improve your decision-making process. With risk-adjusted recommendations and automated workflows, you'll achieve unprecedented productivity, service levels, and cost savings in your supply chain.
With the productization of this patent-pending technology Noodle.ai will become a Generative System of Planning that allows customers to reduce the cost and improve the quality of their supply chain planning by replacing outdated systems.
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