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Chronos
COVID-19 killed over 7 million people. The first pneumonia cluster appeared on November 17, 2019. WHO declared a global emergency 74 days later. CHRONOS exists to close that gap. CHRONOS is a multi-agent AI system that detects novel pathogen emergence across genomic databases, wastewater surveillance, hospital anomaly feeds, and social media — then immediately runs 10,000 parallel counterfactual policy simulations to answer the question no tool answers today: if we had acted on Day 3 instead of Day 47, how many lives would have been saved, and what is the exact response sequence that achieves that? The system runs six specialized agents in a coordinated pipeline: Sentinel (multi-signal anomaly detection), Phylogenetic (GPU-accelerated genome analysis for R0 and IFR estimation), Mobility (human movement network construction from flight and commuter data), Simulation (10,000 parallel agent-based epidemic runs), Policy Optimizer (Pareto-optimal intervention ranking by lives saved vs. economic cost), and a Mutation Risk Agent for variant forecasting. The AMD MI300X is not optional. Its 192GB unified HBM3 memory pool allows the full state of all 10,000 simulation scenarios to reside in a single memory space with zero PCIe transfers. On CPU, this job takes 4.2 hours. On MI300X, it completes in 47 seconds — a 322x speedup. That architectural property is what transforms CHRONOS from an overnight batch job into a real-time decision support system for governments. A judge selects any historical scenario, types a pathogen name and city, and within 60 seconds sees two timelines side by side: the actual government response vs. the CHRONOS-optimal response, with projected lives saved and economic damage avoided displayed in real time. Powered by Gemma 4 via Fireworks AI for policy briefings and pathogen Q&A. Built for health ministries, pandemic reinsurers, and WHO agencies in an $8 billion global market.
13 Jul 2026
