ENERGY & INFRASTRUCTURE
Site Safety & PPE Compliance
Site Safety & PPE Compliance. What it takes to run it.
Automated compliance checks for field crews in hazardous zones.
// 01 · The question
“Was the crew in the right gear for the zone they were standing in?”
// 02 · Why it is hard
Compliance is judged on the worst moment, not the average one, so the frames that matter are the rare ones. A model that is right ninety-nine percent of the time can still miss every violation.
// 03 · What the labels have to be
Bounding box + keypoints
Decided before the first frame
A helmet box and a person box in the same frame do not tell you the helmet is on that person's head. Keypoints put the head, shoulders and waist in known positions, so the gear can be attributed to a body instead of to a scene.
This is the decision that is expensive to reverse. The geometry has to match what the answer contains, and finding out it does not means labelling the set a second time.
// 04 · How we run it
Three parts of one loop, on this job.
LexAnnotate
Pixel-Perfect Data
Annotate power line components, insulators, vegetation encroachment, corrosion, and structural defects with pixel-level precision. Expert-verified for safety-critical accuracy.
LexInsight
Asset Intelligence
Transform isolated defect labels into a queryable asset intelligence graph. Link visual anomalies to asset IDs, maintenance schedules, and SCADA data. Track defect progression over time - not just point-in-time snapshots.
LexAlert
Drift Alerts
Monitor deployed models against seasonal drift, weather changes, and equipment aging. Auto-retrain when accuracy drops, so detection holds as field conditions change.
// 05 · What breaks it after launch
Crews work behind equipment, inside trenches and turned away from the lens. Partial views are the normal case here rather than the exception, and a model trained on clear ones reports compliance it never actually saw.
It is not the only one that can get this use case, it is the one that usually gets it first. All ten conditions.
// 06 · In energy & utilities
Grid Safety & Defect Identification
The Challenge
Severe risk of model degradation caused by rapidly shifting weather patterns, dynamic equipment placement, and evolving site layouts across remote grids.
Our Execution
Engineered safety-critical visual datasets and architected a continuous data ingestion pipeline to instantly process new field imagery as configurations evolved.
The Result
Achieved 21,000+ hazard detections per month, drastically improving frontline worker safety and unlocking frictionless scalability across remote sites.
21,000+
Hazard detections per month