AI optimization
AI that works from your fleet data.
Our AI layer sits on top of the compliance and operational data you already capture. It suggests routes, flags maintenance, scores risk and reads your documents.
Use cases
Where AI helps
Each use case starts from the records your fleet already keeps in Safety Real Time.
Route and cost optimization
Models weigh distance, fuel, hours of service and lane history to suggest routes.
Aimed at fuel and deadhead cost
Predictive maintenance
Inspection defects, mileage and telematics patterns can point to a failing component before it breaks down.
Aimed at fewer roadside breakdowns
Driver risk scoring
Behavior and inspection data show risky patterns, so you can coach drivers.
Coaching before incidents
Document OCR and classification
AI reads BOLs, rate confirmations and PODs, extracts the fields and files them to the right load.
Less manual data entry
Compliance assistant
Ask plain-language questions about DOT rules, due dates and your own records, and generate reports.
Quicker answers and audits
Operational insights
Turn raw fleet data into trends and alerts so managers see what’s changing without building spreadsheets.
Trends and alerts without spreadsheets
How it fits
Built on the data you already keep in Safety Real Time
Because compliance and operations already run in Safety Real Time, the AI layer has connected data to learn from. You turn on the models you want, and the results show up in the workflows your team already uses.
Grounded in your records
Models use your inspections, defects and load history.
Inside existing workflows
Recommendations appear where work already happens: dispatch, maintenance and safety.
Turn on what you need
Start with one use case and add more later. Route, maintenance and risk models are part of the Scale package.
See which models fit your fleet
We will walk through which models fit your operation and what data they would learn from.