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AI Technology

The engine: real-time vision on real job sites.

This page explains what our models see, how they decide, and exactly how AWS and NVIDIA technology is used, not name-dropped.

01 · What the AI sees

Live frames from existing site cameras

Standard IP camera streams in varied light and weather: dust, rain, glare, night work under floodlights. We build and label our violation dataset from footage like this, because models trained on clean stock imagery fall apart on a real site.

02 · What it detects

The violations behind most injuries

PPE compliance per person per frame: hard hats and hi-vis vests. Workers inside exclusion zones near cranes, trenches, and heavy equipment. Blocked emergency exits. Each detection class exists because it maps to a documented cause of site injuries.

03 · How it decides

Persistence thresholds, not single frames

Detection and tracking models classify PPE and follow worker positions in real time. An alert fires only when a violation persists past a set threshold. One odd frame is noise; six seconds inside a crane radius is a hazard.

04 · Why it improves

A feedback loop per site

Every confirmed and dismissed alert becomes labeled training data. The models sharpen for each site's specific cameras, mounting angles, and conditions, so coverage gets better the longer Sentrywork runs.

Pipeline: camera feed, frame sampling, vision models for PPE and zone detection, alert threshold, safety manager dashboard CAMERA FEED FRAME SAMPLING VISION MODELS PPE · ZONES GPU INFERENCE ALERT THRESHOLD MANAGER DASHBOARD
Construction cranes lit up at night over an active site
Night shifts, floodlights, glare: the footage our models are built for.
Infrastructure

How we use AWS and NVIDIA: explained, not name-dropped.

How we use AWS

  • Amazon Kinesis Video Streams ingests live camera feeds from connected sites.
  • Amazon S3 stores confirmed alert clips under each customer's retention policy.
  • AWS Lambda and Amazon ECS run alert orchestration: thresholds, routing, and notifications.
  • Amazon RDS holds violation and compliance records that back the dashboard and exports.
  • Amazon CloudFront serves the dashboard and this site; Amazon CloudWatch monitors uptime and stream health.
  • Amazon Bedrock is planned for future incident summarisation across a site's alert history.

How we use NVIDIA

  • NVIDIA GPUs train our PPE and proximity detection models on labeled site footage.
  • TensorRT optimises those models and Triton Inference Server serves them for real-time, frame-by-frame inference at the rates safety detection requires.
  • NVIDIA Jetson edge devices are our path for low-bandwidth sites: on-site detection without streaming raw video off site.

AWS and NVIDIA are trademarks of their respective owners. Sentrywork is not affiliated with or endorsed by them.

Why now

Three curves just crossed.

Models finally handle site footage

Vision models are now accurate on cluttered, low-light, weather-beaten footage: the kind real sites produce, not the kind demo reels use.

GPU inference is affordable to run continuously

Watching every frame of every feed used to be economically absurd. Optimised inference on modern GPUs makes continuous monitoring a subscription, not a data-centre project.

Insurers want proactive data

Carriers and clients are starting to ask for evidence of proactive safety monitoring, not just after-the-fact incident reports. Sites that can show it have an edge.

Market & traction

Who it's for, and where we honestly are.

Market

  • Target users: general contractors, industrial facility operators, and safety consultancies.
  • Launch markets: [confirm launch geographies]
  • Revenue model: a per-camera or per-site monthly subscription; see pricing.

Traction, stated honestly

  • MVP PPE detection in development
  • Piloting on a small number of active sites
  • Building the labeled violation dataset from real footage
  • Waitlist open for contractors and operators
Roadmap

Where this is going.

MilestoneWhat it deliversStatus
MVP PPE detectionHard hat and hi-vis vest checks on live feeds, alerts with clips.In development
Pilot & dataset buildFirst sites live; labeled violation dataset grows from real confirmations.In progress
Zone & proximity alertsExclusion zones around cranes, trenches, and vehicle routes.Next
Blocked exit detectionAlerts when emergency exits and escape routes are obstructed.Next
Edge & offline processingNVIDIA Jetson devices for low-bandwidth sites; no raw video leaves site.Planned
New market expansionBeyond launch geographies and into adjacent industrial verticals.Planned

See it on your cameras.

Book a walkthrough and we will show you what Sentrywork would catch on a site like yours.