Dilygence is a simple an intuitive tool; you'll spend less time on paperwork and more time on prevention!
Improve you assessment and your results with the help of a powerful set of features.
Modernity as a service
Dilygence is a cloud-native software available on a web browser on your PC or tablet. Work with a restful mind anywhere, anytime.
Cutting edge risks assessment
Dilygence is cutting-edge web and digital technology. Built in a cooperation with Prévibois, an association of experts in safety and prevention, Dilygence promises to redefine the way you assess risks and prevent them in your workplaces.
An outstanding methodology
The risk assessment methodology used by Dilygence is one of the best in the industry. It has been perfected over many years by the Association de Santé et Sécurité des Pâtes et Papiers du Québec (now Prévibois). Dilygence if the only software based on this methodology.
Prioritize your interventions
Following the analysis of your tasks and machines, you will benefit from a global overview of the situation. Dilygence offers powerful search tools that will allow you to to efficiently target important data and build the necessary plans to reduce risks directly at the source.
Benefit from an overview of your security using graphs and dashboards. In a heartbeat, the key performance indicators will help you orient your decisions. The report system will help you export your data in a coherent and visually pleasant look.
Actions and corrective measures
Security applications require a special attention and that is exactly what Dilygence proposes through its efficient management system. Follow-ups and traceability are easy, and the entire process is simplified, from assigning a manager to adding proofs and documents.
Sharing and trainings
Prevention is at the heart of our preoccupations and sharing is a critical method for improving the performance of security interventions.
Our data libraries will help you get set up and running quickly and our sharing mechanisms vastly improve the security aspect of trainings from existing data.