Advantage through AI
adago: self-learning digital twins to improve your business!
Until recently, many leading manufacturing firms regarded their supply chain as essential but not central to their core business operations. However, amidst growing geopolitical uncertainties, this perspective has undergone a profound shift. Today, supply chain resilience stands as a paramount challenge. Leveraging the wealth of data amassed over the past decade and integrating cutting-edge artificial intelligence advancements, adago crafts a new kind of self-learning supply chain twins based on reinforcement learning. These innovative solutions empower our clients to enhance their comprehension of the supply chain and strengthen their capacity to respond effectively to unforeseen events.
There are good reasons that slow down the use of modern artificial intelligence methodes in supply chain operations. Supply chain processes inherently connect various departments, spanning from production via IT to sales. To cultivate solutions that truly add value, it's imperative to bridge the gap between business understanding, data infrastructure, and AI technology. It is the DNA of adago to not only develop technology but to steer the development so that different groups of stakeholders can improve their daily business routines.
Data engineering is a pivotal factor in the implementation of artificial intelligence across various applications. While generative AI can effectively learn from publicly available data, applying artificial intelligence to the supply chain necessitates a more direct engagement with client-specific data. Whether leveraging AWS, Azure, Palantir, or other data platforms, substantial groundwork has been laid in refining data ecosystems in recent years. Despite these advancements, many solutions in the market predominantly limit themselves to visualizing data through dashboards, offering minimal value addition. adago sets itself apart by taking a more comprehensive approach. Our solution is to create a virtual representation of the business that goes far beyond representing data in dashboards.
Adago's groundbreaking innovation lies in the development of self-improving digital twins. This concept revolves around leveraging object-oriented data structures in line with the Python library gymnasium to organize supply chain data. This organization facilitates the creation of a virtual replica of the actual supply chain, enabling a continuous process of virtual trial-and-error improvement. Distinctive to adago's approach is the ability to optimize these digital twins without any impact on the physical environment. This unique methodology allows for the simulation and learning of adaptive responses to unforeseen scenarios. Examples of such scenarios include simulating a naval blockade of the Suez Canal or sudden fluctuations in demand, providing valuable insights and strategies without real-world consequences.
AI algorithms, employing trial-and-error methods, fall within the realm of reinforcement learning, a captivating frontier in recent AI advancements. As human beings, we've all undergone a similar learning process as infants, using trial-and-error and external reward signals to reinforce positive actions. In our self-learning digital twins, the virtual supply planner assumes the role of a learner, accumulating insights through hundreds of millions of virtual planning steps to adeptly handle diverse situations. At adago, we leverage state-of-the-art algorithms, such as the deep actor-critic PPO algorithm, to train the virtual supply chain agents. Our team of data scientists continually refines these algorithms, tailoring libraries to incorporate problem-specific features. This ongoing research empowers our solutions to address the unique challenges faced by our clients, ensuring adaptability and optimization in the ever-evolving business landscape.
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moritz.kern@adago.de
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