Noonlight, a trailblazer in intelligent emergency response and professional monitoring, has unveiled two groundbreaking enhancements to its Verify API. These innovations, designed to power its cutting-edge video monitoring solution, promise to deliver smarter, more proactive protection for both commercial and residential video security providers and their end-users.
The Verify API integrates a crucial human verification layer into video-triggered events. This allows Noonlight’s highly trained agents to meticulously review incidents before emergency services are dispatched. By seamlessly blending advanced analytics with professional monitoring, Verify drastically reduces non-actionable video “noise,” enabling agents to identify and respond to genuine threats with unprecedented speed – all without increasing operational burden or the costly issue of false dispatches.
The newly launched Verify features include **AI Person Filtering**, an intelligent system that automatically screens incoming video events. This advanced AI dismisses any clips where no person is detected, effectively eliminating the time and cost associated with reviewing empty motion alerts. When an event is escalated to a live monitoring agent, **Advanced Verification** kicks in, providing deeper context through extended footage and live camera access. This empowers agents with the ability to proactively deter a situation in real-time, often before an alarm is even created. The ultimate outcome? Fewer disruptions for users, a significant reduction in unnecessary police dispatches, and dramatically faster alarm resolution when it truly counts.
“The burden of responding to an emergency should never fall on the end user, and unnecessary disruptions should never affect the people our partners are trying to protect,” stated John Tassone, President of Noonlight. “What we’ve built is a smarter way to deliver the right context to agents at exactly the right moment — so they can filter out the noise, act decisively on real situations, and prevent emergencies from escalating wherever possible. That’s what automatic safety looks like in practice.”
AI Person Filtering: Precision in Every Pixel
Noonlight’s proprietary AI model meticulously scans all incoming video clips, automatically dismissing any event where a person is not detected. This ensures that non-actionable footage never reaches monitoring agents. By scrutinizing hundreds of frames per clip, Noonlight’s AI model is engineered to detect even the briefest human appearances, boasting an impressive 99% recall and 97% precision. This means it almost never misses a person and is almost always correct in its detection.
For partners already utilizing AI-based filtering, Noonlight’s model provides incremental noise reduction, especially potent in challenging outdoor environments. Furthermore, it offers the added benefits of vendor consolidation and a reduction in the number of integrations to manage, streamlining security operations.
Advanced Verification: Context, Deterrence, and Real-Time Control
It’s a common misconception that every event requiring video verification necessitates an emergency dispatch. Advanced Verification dramatically enhances Noonlight’s existing verification workflow by granting agents access to critical additional context. This includes extended footage captured up to 90 seconds before the event and a live camera look-in, enabling agents to more quickly and accurately identify potential threats or emergency situations.
Crucially, when appropriate, agents can now initiate active deterrence through direct talkdown via the camera. This powerful feature allows them to de-escalate situations before alarms are even triggered and emergency response is dispatched, potentially averting incidents entirely.
This deeper contextual understanding translates into faster intervention and a superior user experience, all without compromising safety and security. Early data from advanced verification with talkdown reveals a remarkable 45% reduction in total false alarms. In 37% of cases, the person left the scene independently, while in another 8%, agents confirmed the individual was an authorized employee – successfully preventing unnecessary alarms while ensuring genuine threats are never overlooked.