As part of our continuous efforts to enhance integration capabilities and interoperability with industrial enterprise systems, we are excited to announce the latest release of our platform integration capability.
Building on our seamless integration with external data sources, business applications and enterprise systems, we are introducing a dedicated APS Connector Library that integrates Cosmo Tech AI-Simulation software with Advanced Planning and Scheduling (APS) software for optimizing industrial systems and decision making.
The Cosmo Tech APS Connector Library offers several pre-built connectors and the ability to integrate with popular supply chain planning solutions such as Kinaxis, Blue Yonder, OMP and SAP IBP. This allows decision makers to tap into the advanced AI-Simulation experiments’ capabilities for better insights and informed decisions that consider uncertainties, constraints and complex trade-offs.
Furthermore, the Cosmo Tech AI-Simulation Platform provides the freedom to build custom-function connectors, ensuring ongoing data compatibility and adaptability. Users can align data and information with tailored requirements, workflows and processes, extending the functionalities of both the AI-Simulation and APS software. This customizable approach allows decision makers to have maximum flexibility and significantly enhance their abilities in solving complex supply chain challenges, ultimately driving better business outcomes.
By integrating AI-Simulation technology into existing supply chain planning software, businesses can eliminate data silos and gain an accurate and holistic view of inventory levels, supplier performance, production resources, and more. This enhanced and comprehensive view not only improves data quality and scope of analysis but also provides the flexibility to adapt to market dynamics and disruptions within the supply chain. Decision makers can make informed decisions based on accurate data and identify the best course of action for improved efficiency, risk management and overall supply chain performance.
