The new model unlocks breakthrough platform capabilities including Agentic Video Walls, Activity Notifications, and Semantic Search, delivering agentic monitoring and investigations for enterprises.
Ambient.ai announced the general availability of Ambient Pulsar, its most advanced AI architecture to date. Designed to replicate the reasoning abilities of an expert security operator, Pulsar processes visual information at machine speed and enterprise scale. Trained on more than one million hours of ethically sourced video and capable of analyzing over 500,000 hours per day, Pulsar is now the largest vision-language system deployed in the physical security sector.
Cary Monbarren, Senior Director of Corporate Security at SentinelOne, stated “with Pulsar, Ambient.ai has built what every enterprise security leader has been waiting for: an AI that’s not just fast, but intelligent. This platform is transforming how GSOCs operate, drastically reducing manual triage and response times.”
Shikhar Shrestha, CEO of Ambient.ai, added “Pulsar marks the beginning of a new era for physical security—one where AI doesn’t just detect, but truly understands and acts.”
Pulsar is engineered as a next-generation, edge-optimized VLM that merges perception, semantic understanding, and autonomous reasoning. Unlike legacy analytics or detector-based systems, Pulsar operates continuously at the edge, enabling real-time, scalable performance across thousands of live streams.
Ambient.ai’s platform now integrates monitoring, threat assessment, access intelligence, investigations, and orchestrated response beneath a unified AI engine. Enterprise customers across Fortune 100 technology, aerospace, finance, manufacturing, pharma, and critical infrastructure are reporting up to 95% reductions in false alarms and an 80% reduction in alert-handling times—driving substantial operational savings.
With Pulsar at the platform’s core, Ambient.ai aims to redefine what modern enterprise protection looks like: intelligent, autonomous, adaptive, and capable of preventing incidents before they escalate.
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