Industrial and workplace safety
Annotation, QA and iterative refresh for safety AI and industrial site intelligence, from PPE and pose to forklift and pedestrian interactions.
Who it is for
Safety AI platforms building models for industrial sites, industrial operators running their own computer vision programmes, and EHS and implementation partners who need reliable training data behind a deployment.
Typical problems
Industrial footage is crowded, partly occluded and filmed from awkward overhead angles. Typical labelling needs include:
- PPE compliance: helmets, vests, gloves and other equipment, by body region and colour.
- Near-miss and behaviour labelling: unsafe acts and close calls on CCTV.
- Forklift and pedestrian interactions: vehicles, people and the space between them.
- Zone control: people and vehicles in restricted or marked areas.
- Industrial pose estimation: keypoint skeletons for posture and activity.
What we can do
Computer Vision annotation, QA and iterative refresh for industrial site-intelligence models, so datasets keep pace as sites, cameras and rules change. We can label from scratch, check and correct existing labels, or run a rolling programme that refreshes the dataset as new footage arrives.
Proof
Three concurrent projects for the same confidential EU client, each run with two-tier review:
- Human pose keypoint annotation: more than 250,000 skeletons.
- PPE compliance: more than 3.4 million region-of-interest tags.
- Workplace safety object detection: more than 6 million instances.
Delivery and security
Work is checked through two-tier review, and data is handled as agreed with you in writing before work starts. See How We Work and Security and Compliance.
Request a Project Quote
Planning a workplace-safety dataset, or need an existing one checked? Tell us about the footage, the classes and the sites.