Implement Real-Time AI Safety Monitoring for Your Job Site

Small construction firms rely on project management software like Procore or daily reporting tools like Raken. These platforms are excellent for documenting what has already happened. A supervisor uploads daily site photos, and a safety manager reviews them that evening, spotting a subcontractor without a hard hat. The problem is the 8-hour delay; the system is a historical record, not a preventative tool.

Consider a 15-person general contractor with a supervisor managing three active sites. The supervisor does hourly walkthroughs. In between those rounds, a new crew begins work near an unprotected edge without proper tie-offs. The risk exists for 45 minutes before it is manually discovered. Existing software has no mechanism to flag this because it relies entirely on human input. It cannot watch the site for you.

Even dedicated safety platforms like SiteDocs digitize safety forms and compliance paperwork. They streamline reporting but do not offer live observation. The fundamental architectural issue is that these systems are databases designed for user-initiated data entry. They are not event-driven systems capable of processing unstructured video streams to identify and react to events as they unfold. They are built to store reports, not generate real-time warnings.

An engagement would begin with a risk audit. Syntora would work with your site supervisor to identify the top 3 preventable safety issues and inventory your existing IP cameras. We would confirm camera angles and resolutions are sufficient for detection and map out the exact zones and rules, such as 'a person detected without a hard hat inside the red-taped foundation area triggers a high-priority alert.'

The technical system would pull frames from your camera RTSP streams every 5 seconds using a service running on AWS Lambda. Each frame is processed by a computer vision model trained to identify people, hard hats, and safety vests. If the model detects a violation with over 95% confidence, it triggers an event. That event is handled by a FastAPI service, which logs the incident with a snapshot image to a Supabase database and sends an immediate SMS alert via Twilio to the supervisor. This entire process, from detection to alert, would take under 10 seconds.

The delivered system is a private dashboard for reviewing all flagged events, accessible on a phone or tablet. Each event includes the time, location, risk type, and a photo of the infraction, creating an automated compliance log. The system requires no new hardware, using your existing cameras. Hosting costs for a 3-camera site would typically be under $50/month.