sec.gov/Archives/edgar/data/2084806/000149315226008823/formf-1a.htm The global market size of Supply Chain Visibility and Execution Software Platform was valued at USD8,233.5 million in 2024 and is estimated to register a CAGR of 13.5% between 2025 and 2029. Supply Chain Visibility and Execution Software Platforms are benefiting from rising supply chain complexities, e-commerce growth, sustainability mandates, cost pressures, and global trade expansion, necessitating real-time visibility and risk mitigation. These platforms leverage Al, cloud technology, and data integration to address disruptions, optimize operations, and ensure compliance with stringent ESG regulations. In 2024, manufacturing and retail & e-commerce segments held the market shares of approximately 25% of the overall global market size of Supply Chain Visibility and Execution Software Platform analytics, natural language processing, and computer vision, enabling data processing, automated decision-making, and actionable insights. This shifts reactive systems to proactive, intelligent ones, tackling disruptions, inefficiencies, and demand fluctuations. AI is incorporated via modular components like embedded algorithms in dashboards, APIs for data integration, and edge computing for real-time processing, allowing seamless upgrades to existing platforms without complete replacements. > Real-Time Tracking and Monitoring: AI algorithms process data from sensors, GPS, RFID, and IoT devices to offer granular visibility into shipments, inventory, and assets. For instance, computer vision analyzes images or videos for anomaly detection (e.g., damage or delays), while ML models correlate data streams to ss h s ns eo asn , n ssn tsd s d s a sn proactive adjustments. > Predictive Analytics and Risk Mitigation: AI integrates predictive models to forecast risks and trends. ML analyzes historical data, market signals, and external factors (e.g., social media sentiment or geopolitical events) to identify potential bottlenecks. This enables features like automated alerts for supply shortages or compliance issues, reducing forecasting errors by up to 40%. Infor Nexus, for example, employs AI-enhanced dashboards for end-to-end visibility, flagging risks in the “First Mile” of production. https://www.sec.gov/Archives/edgar/data/2084806/000149315226008823/formf-1a.htm