CASE STUDY:

Shawmut uses AI to manage project risk at scale

GET THE CASE STUDY

    Key Features

    Safety Observations
    • Empower safety teams with easy-to-use tools, get them out into the field doing observations, and make safety “everyone’s job”.
    • Drive attention to both positive and negative field conditions and behaviors.
    • Measure observation compliance across the company with metrics.
    Safety Monitoring
    • Use construction-tuned AI to uncover signals of risk in your project data and media, focusing attention on the most at-risk projects.
    • Use pre-built integrations with Autodesk, Procore, Oracle, and other systems to feed data to Vinnie the construction-tuned AI engine.
    • Vinnie automatically scans existing project data for signals of risk, including calculating compliance metrics and performance benchmarks.
    Predictive Analytics
    • Use the outputs of the Safety Monitoring module, along with other project data to provide a risk “score” to predict which projects are most at- risk for an incident.
    • AI models finely-tuned for your company alert safety teams of risks a week ahead of time, reducing incident rates through proactive management.

    “The trend data we’re getting from Vinnie is helping us figure out where we need to focus our attention.”

    - Shaun Carvalho, Vice President of Safety, Shawmut