Real-time Analytics
Leidos needed to reduce information overload and improve coordination in fast-moving disaster scenarios where human commanders must ingest video, radio, sensor, and public-safety signals quickly enough to allocate resources before conditions change.
Reported impact
The multi-agent system gives commanders faster, more accurate situational awareness, reduces cognitive load on responders, and lowers the cost of development and rollout by using GPU virtualization while improving coordination across multiple agencies during emergencies.
Leidos and NVIDIA built a multi-agent emergency-response command center that aggregates radio-frequency, audio, video, and tactical data into a single operational picture. AI agents analyze roadway and public cameras, weather feeds, emergency vehicle locators, automated 911 transcripts, and radio communications, then summarize and route those observations through tactical guidance software for a human commander. NVIDIA NIM and NVIDIA AI Enterprise package and govern the generative services, while NVIDIA Metropolis supports the video analytics layer and NVIDIA vGPU with RTX Virtual Workstation speeds development and test on modest infrastructure. Instead of relying on static models and manual triage, the command center uses interactive orchestration so a human decision-maker can ask for context, hand work to specialized agents, and get near-real-time recommendations about the regions, assets, or citizens that need attention first.
Video, RF, audio, weather, vehicle-location, 911, and radio feeds are aggregated into the command center, analyzed by AI agents and video services, combined with tactical guidance software, and presented through an interactive agent that helps the human commander coordinate action.
The AI agents processing data from roadway intersection cameras, weather data, public camera feeds, emergency vehicle locators, automated 911 transcripts, and radio communications are combined with tactical guidance software.
The system reduces cognitive load, boosts situational awareness, and enables coordinated response across multiple agencies.
Virtualization with NVIDIA virtual GPU (vGPU) accelerates AI development and testing on modest hardware, cutting rollout time and infrastructure costs.
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Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
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