
LookDeep Health has unveiled advanced AI capabilities designed to bolster the safety of hospital care teams by shifting from reactive notification to proactive prevention of workplace violence.
The AI-driven platform now employs video-based security protocols to identify and avert potential attacks.
Representing 10% of the labour force in the US, healthcare workers experience around half of all reported non-fatal workplace violence injuries.
With two nurses assaulted every hour in acute care settings, incidents such as the February 2025 hostage situation in a Pennsylvania ICU underscore the urgency of safeguarding those who provide essential care.
LookDeep founder and CEO Narinder Singh said: “Tension builds through agitated movements, raised voices, and escalating behaviours. Clinicians sense rising danger and may call for help. If uninterrupted, these situations can quickly turn harmful.
“With AI, we can support clinicians exactly when they call for assistance—and even earlier—by sensing risk and providing an extra set of eyes or timely intervention to help de-escalate before an incident occurs. We can use the same technology hospitals already need for telemedicine to better care for the nurses and doctors that care for our loved ones.”

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By GlobalDataThe LookDeep platform’s new features aim to protect nurses, clinicians, staff, and patients from violence within healthcare centres.
These innovations include voice-activated help requests, allowing staff to discreetly or overtly signal for assistance.
AI-powered situational awareness tools transform existing video infrastructure into a continuous safety net, offering ambient awareness and flagging rooms with escalating tensions before help is requested.
Additionally, the integration of real-time location systems (RTLS) with wearable badges enables staff to silently summon aid when in distress.
When combined with the AI-driven LookDeep platform, hospitals can connect their systems to detect and respond to threats with greater speed, enhancing overall security and response times.