Traditional camera systems have a fundamental flaw: they rely on basic motion detection, bombarding users with irrelevant alerts triggered by swaying trees, passing insects, or even shifting shadows. This isn’t just inefficient—it’s a distraction from real threats.

Enter tl;dw, an advanced API leveraging cutting-edge video language models (VLMs) to transform security video feeds into actionable intelligence. It’s not about adding more cameras or capturing more footage; it’s about understanding what’s happening and why it matters.

Our system doesn’t just detect motion—it recognizes and interprets objects, behaviors, and context. Imagine receiving an alert only when there’s something worth your attention, like a potential threat, a suspicious vehicle, or an unauthorized individual. By filtering out noise, we’re redefining what “smart” really means in security.

tl;dw works with existing IP camera setups, upgrading them with advanced capabilities like license plate and facial recognition. High-resolution footage ensures every detail is captured, providing a robust foundation for proactive security.

The benefits go beyond detection. With tl;dw, security teams can:

• Verify alarms quickly and accurately.
• Review footage with contextual insights.
• Dispatch responses more efficiently.
• Escalate critical events to supervisors with precision.

By automating repetitive tasks, tl;dw reduces operator burnout, minimizes missed incidents, and enables teams to focus on what truly matters: protecting people and assets.

As AI continues to reshape industries, the security sector has an opportunity to lead by example. tl;dw empowers personnel to upskill, shifting their focus from monotonous monitoring to meaningful, strategic action. This isn’t just about efficiency—it’s about transforming security into a proactive, highly adaptive force for good.

Security leaders have been asking for a way to scale operations without sacrificing quality or escalating costs. With tl;dw, that vision is finally a reality.