CASE STUDY:

Shawmut uses AI to manage project risk at scale

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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