SafetyFirst
An OH&S platform that predicts workplace incident probability over the next seven days, so prevention has somewhere specific to go.
- Workplace Operations
- Deployed on IBM Watson
- PythonXGBoostIBM WatsonFastAPI
- People's Choice Award, SaskHack 2026
7 days
Forward prediction window
Safety programs are measured on incidents that already happened.
Lagging indicators tell an organisation where it failed, months after the failure. The information that would have predicted the incident — who was on shift, what the conditions were, what the site's history looks like — exists at the time it would have been useful, and is never assembled into a probability anyone can act on.
- 01
Assemble the real inputs
Worker characteristics, current conditions, and historical patterns are brought together as one feature set rather than three separate reports.
- 02
Model the probability
An XGBoost model trained and deployed on IBM Watson scores incident probability over the following seven days.
- 03
Serve it where work is planned
Predictions are exposed through a FastAPI REST API, so the score reaches scheduling and briefing tools rather than a dashboard nobody opens.
- 04
Act inside the window
A seven-day horizon is chosen because it matches how shifts and site work are actually planned.
- 01
Inputs
Worker characteristics, current site conditions, historical incident patterns
- 02
Features
Combined feature set aligned to a seven-day forward window
- 03
Model
XGBoost, trained and deployed on IBM Watson
- 04
Serving
FastAPI REST API returning incident probability
- 05
Surface
Predictions delivered into planning and briefing workflows
Safety attention is allocated by predicted risk rather than by last quarter's incident log.
The model outputs a seven-day probability per context; the score is inspectable.
The prediction lands inside the planning window it is meant to change.
Verifiable directly: predictions are served over a REST API at planning time.
The approach holds up to outside scrutiny.
People's Choice Award, SaskHack 2026.
- Seven-day incident probability prediction
- Worker, condition, and history feature modelling
- XGBoost model training and deployment
- IBM Watson hosted inference
- FastAPI REST prediction service
- Integration into existing planning workflows
Safety officers
Deciding where to focus a limited number of interventions this week.
Site supervisors
Adjusting crew and task assignment against current conditions.
Operations leadership
Seeing risk concentration across sites before it becomes a claim.
This page does not fabricate product imagery. The slots below are reserved at their final dimensions and name exactly what is needed.
Risk view for one site across the seven-day window.
A real prediction response from the REST API, redacted.