First Project : Tech bricks to Improve Fleet and Asset Management in Logistics
We developed a SaaS platform to collect and process the data gathered by our client.
This initial project aims to create a suite of software applications that use Deep Learning algorithms to understand and interpret user input, feedback from past experiences, and worker behavior.
This enables the handling of complex queries and the prediction of future needs.
Our AI-based algorithms evaluate numerous hard and soft constraints to match worker skills with major, minor, and critical tasks. This ensures the creation of relevant schedules and directs users to appropriate resources.
This approach has offered several benefits:
- Improved routing to optimize fuel usage and prepare for the adoption of new fuel types (bio/electric vehicles).
- Automated maintenance processes, reducing diagnostic costs through predictive maintenance.
- Enhanced fleet planning to anticipate future demand and deliver higher service levels.
With the integration of sensor technology, historical data, and advanced analytics, our fleet management software provides a unified view of the entire ecosystem, optimising various operational aspects such as:
- Fuel costs and usage per route
- Idle time
- Compliance violations
- Driving time affected by traffic, road, or weather conditions
- Driving behavior
- Security
- Maintenance schedules and the delivery of required parts