Supply Chain 2.0 for Semiconductors

Build a production-ready AI platform that gives semiconductor companies and their customers real-time visibility, predictive intelligence, and automated resilience capabilities across the global chip supply chain. Core vision: Create an AI-native supply chain intelligence and execution platform specifically for semiconductors — where supply chains are uniquely complex due to multi-year lead times, geopolitical concentration risk (TSMC, ASML dependencies), extreme capital intensity, and the cascading downstream impact of even small shortages. The platform predicts disruptions months in advance, automatically identifies mitigation strategies, and executes procurement actions to keep production lines running. The system must support the full semiconductor supply chain lifecycle: 1. Map the complete supply chain from wafer to finished chip 2. Monitor risk signals across fabs, substrates, equipment, and logistics 3. Predict shortages and lead time changes 6-18 months ahead 4. Generate mitigation options with cost and feasibility analysis 5. Execute approved procurement and production changes 6. Continuously improve forecast accuracy from outcome data Core capabilities: Supply chain mapping and visibility: - Model the complete supply chain: wafer, reticle, substrate, OSAT, test, logistics - Track node-level capacity at leading fabs (TSMC, Samsung, Intel Foundry, SMIC) - Map substrate and advanced packaging supply (ASE, Amkor, JCET) - Monitor critical material availability (photoresists, CMP slurries, noble gases) - Track equipment lead times for capacity expansion projects - Identify single points of failure and geographic concentration risks Risk monitoring and signals: - Monitor fab utilization rates from earnings calls and analyst reports - Track geopolitical developments affecting Taiwan, South Korea, Japan, Netherlands - Watch export control changes affecting design tools and advanced equipment - Monitor natural disaster, power grid, and water supply risks at fab locations - Track competitor demand patterns that create capacity competition - Follow commodity prices for key materials and process chemicals Predictive analytics engine: - 6-18 month lead time forecasting by node, package type, and geography - Shortage probability scoring with confidence intervals and scenario analysis - Allocation prediction: when will fab customers be put on allocation? - Price trend forecasting for wafers, substrates, and test capacity - Yield risk modeling based on fab process maturity and defect density trends - Scenario modeling for specific disruption events (Taiwan strait, export controls) Mitigation and procurement optimization: - Inventory buffer strategy optimization with carrying cost vs. risk tradeoffs - Alternative sourcing analysis: mature node substitution, design porting feasibility - Long-term agreement (LTA) negotiation timing recommendations - Spot market vs. contract allocation strategy optimization - Capacity reservation recommendations at foundries and OSATs - Demand-side options: product redesign triggers, customer allocation planning Execution and workflow automation: - PO generation and submission to approved foundries and distributors - Expedite request management with priority scoring - Supplier communication automation for forecast updates and capacity requests - Customer allocation calculation and notification workflows - Design-win registration and capacity pre-reservation workflows Build a working demo covering: 1. View the supply chain map for a hypothetical SoC showing all dependencies 2. Simulate a Taiwan fab capacity reduction and see downstream impact 3. View 12-month lead time forecast for advanced packaging at top OSATs 4. Generate a buffer inventory recommendation with cost/risk tradeoff 5. Trigger an automated procurement workflow and see generated PO