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During mass-casualty events or natural disasters, human dispatchers become severely overwhelmed by chaotic, unstructured reports . Crucial seconds are lost parsing text, mapping locations, and finding the right medic, which causes delayed response times when seconds mean the difference between life and death dispatchAI is a next-generation autonomous emergency grid powered by AMD designed to eliminate this human bottleneck . It provides autonomous coordination at scale by using Natural Language Processing to instantly ingest unstructured emergency reports via Telegram webhooks . Our system scales to handle 10 simultaneous mass-casualty incidents in under 10 seconds, successfully reducing average dispatch latency by 90% . The architecture operates as an Event-Driven Asynchronous Pipeline, utilizing a FastAPI backend and a tactical React/Vite dashboard . At its core is the "AMD Brain," which is powered by AMD Instinct™ MI300X Accelerators running the Qwen2.5-14B-Instruct model . We chose this model because it offers the perfect balance of deep reasoning for complex medical routing and high inference speed directly on AMD hardware . The LLM is rigorously prompt-engineered to align with human dispatcher logic, matching the exact skills needed with the closest available volunteer . Furthermore, the system includes dynamic "Follow-Up" logic via Telegram to clarify vague emergencies, and features a 15-second graceful fallback to pure proximity math to ensure enterprise reliability without AI hallucinations . DispatchAI ensures the right help arrives exactly when it is needed

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