RootBlockLabs builds Computer Vision solutions that turn the cameras you already have into a live detection layer — reading PPE compliance, vehicle movement, and restricted-zone activity in real time, instead of just recording it for someone to review later.
Most industrial cameras today only do one job: record, so that someone can review footage after something has already gone wrong. Computer vision changes what the camera is for — the feed is interpreted as it happens, not archived for a post-incident investigation.
AI video analytics is what happens when a camera feed is run through a trained model instead of just a monitor. At the center of it is image recognition — the model learning to classify what's actually in a frame, whether that's a hard hat, a forklift, or an empty walkway that should be occupied.
RootBlockLabs layers detection and tracking on top of that recognition step, so the system understands not just what's in a single frame, but what's changing across frames over time.
Four capabilities, combined differently depending on the site.
Identifying and classifying people, vehicles, and equipment in a frame — the foundation every other capability below is built on.
Flagging missing helmets, vests, or gloves in a monitored zone, in real time rather than during a periodic walk-through.
Catching inconsistencies on a line or in a finished part at the point of production, not after it has shipped.
Watching a defined boundary continuously and alerting on entry, without a guard physically stationed there.
A single detected object is a data point. Object tracking is what turns it into something useful — following a specific vehicle, person, or item across multiple cameras and over time, instead of treating each frame as unrelated to the last. How that gets applied depends on the site.
Defect detection catches a damaged part or a misaligned component at the point it occurs on the line, rather than at final inspection. Paired with ongoing quality inspection across shifts, the same cameras that watch the line for safety can watch it for consistency too.
See Edge AI for manufacturing.Vehicle detection tracks forklifts, trucks, and trailers across a yard or dock, flagging near-misses with pedestrians and confirming which bay a vehicle actually used, without someone reviewing hours of footage after the fact.
See Edge AI for energy.PPE detection is usually the first capability a construction site deploys, since the risk is constant and the site changes daily. It covers helmet, vest, and harness compliance across active work zones, feeding straight into existing safety reporting rather than replacing it.
See Edge AI for construction.Most site security deployments run on video surveillance analytics that watches entry points and restricted zones continuously, flagging activity a guard roster alone would miss on a night shift. Facial recognition sometimes comes up at this stage, and it isn't part of a standard deployment here — it's treated as a separate capability, used only where legally appropriate and scoped through its own legal and compliance review, not bundled in by default.
See our crowd management solution.The model runs on edge hardware at the site, not in the cloud, so what you get is real-time video analytics: a detection in the current frame triggers an alert in that same moment, instead of after a round-trip to a remote server. That's also what keeps it working when the site's connection drops — see Edge AI for how the inference itself runs on-site.
Five quick questions about your existing cameras — see where you likely stand before a site assessment.
Computer vision is AI that interprets what a camera sees — identifying objects, people, vehicles, or conditions in a video feed — instead of just recording footage for someone to review later. RootBlockLabs runs these models on-site, close to the camera, so detections happen in real time.
Talk to an engineer about which cameras and zones are the best fit for computer vision first.
A site assessment, not a sales pitch, scoped before any commitment.