Suffolk Construction - RiskX Dashboard

    Case Study: Using culture and technology to reduce the Recordable Incident Rate

    Suffolk Construction
    Safety Observations

    Suffolk Construction provides a great example of the power of a strong safety culture and how a well designed program can further strengthen it. Using their national safety program, RiskX, and technology partner,, they were able to reduce recordable incidents by 28% and cut lost time by 35% within 12 months. 


    Vinnie identifies ladder use, consistent with elevated risk.

    Case Study: Using 360 photos, reality capture and AI to save time and reduce safety risk

    Barton Malow
    360 photos and video and AI

    Barton Malow is deploying products as part of a pilot program. The Safety Observations product combines an easy-to-use mobile application with risk scoring and workflow that enables the entire company to engage in gathering safety data. The Predictive Analytics product analyzes both the AI-based Safety Monitoring and Safety Observation data sources, in addition to other project data, including 360 photos from StructionSite, to create prioritized project rankings so teams know where to focus attention.


    Safety Monitoring module

    Case Study: Using AI to manage project risk at scale

    Shawmut Design & Construction
    Enterprise risk dashboards

    Learn how Shawmut Design & Construction implemented the Safety Monitoring module across all projects to reduce risk by automatically identifying projects deserving of additional safety team oversight.  Vinnie, the construction-trained AI, created data that feeds a project-ranking dashboard, used weekly by the team to prioritize their focus.  


    Learning to predict and prevent construction incidents

    Case Study: Learning to predict and prevent construction incidents

    Predictive Analytics

    Artificial Intelligence is now being applied across industries at many levels of technological sophistication. From automotive robots that can “see” what to weld to medical devices that warn doctors of risks during surgery, computers that can observe the world around them.  This case study explores how these approaches are being applied to the world of construction safety risk, with exciting results.


    Reducing risk and improving safety

    Case Study: Reducing risk and improving safety

    Autodesk BIM 360 integration

    Skanska USA is one of the largest construction and development companies in the U.S., serving a broad range of clients including those in transportation, power, industrial, water/wastewater, healthcare, and more.  In this case study, learn how they are using Smartvid to help reduce safety risk as a contractor and an owner.



    “RiskX combined with our strong safety culture and technology from gives us consistent, predictable performance with continuous improvement.”


    “By having an “extra pair of eyes that doesn’t sleep” looking at our photo data, we could better identify both positive examples and areas for improvement that we might otherwise miss and grow our safety library. We’re also exploring how to tie technology into our proprietary EHS planning platform called PlanIt, in order to mitigate risk prior to worksite tasks taking place.”

    Barton Malow

    “As we grow and continue to capture more and better data on our jobsite conditions, worker behaviors, and incidents, AI is helping us better understand and proactively manage safety risk across our jobsites.’s image recognition and predictive analytics are two super-powerful, yet extremely practical and easy to use AI applications that we’re excited to be investing in.”

    Shawmut Design and Construction

    “Smartvid complemented our human-based observations with a third-party AI perspective. Both are necessary for understanding risk and deciding where to focus our attention. For example, when Vinnie found a high rate of housekeeping issues on an otherwise well performing project, we immediately reviewed examples and found the project had begun demolition, creating piles of debris and standing water. We provided additional resources to the site, including a tool box talk, as the project had now entered this higher risk phase. Without Vinnie, we never would have known to give the project some added support.”


    “After the pilot project, we were convinced these new techniques create additional value for our clients by enabling a quantitative assessment of key infrastructure health indicators like cracks. In the future, we look forward to expanding these models to other indicators of damage, including concrete spalling and water ingress features.”


    “Right now in the machine learning and AI space, photo recognition is one of the most proven technologies that has really come out in the last year.”


    “ saves us lots of time but also gives us a much better way of capturing the visual record of what we do everyday. All of the tags that finds go into Procore as descriptions in the photos so they are searchable immediately. This reduces the amount of time field personnel have to spend and removes any need for re-entry into Procore. It’s a win-win. Our field teams can save time and our other team members see the information show up automatically in Procore so they don’t need to learn another system.”

    Shawmut Design and Construction

    “Data from OxBlue, Procore, and our 360 photos coming together and being used to identify indicators of risk is a key benefit of the Smartvid system. No person could ever review all of those photos, but with Vinnie, we can use them to look for signals of risk.”

    Barton Malow

    “Vinnie helps us tap into the full value of the images we already have, with no added resource required. Reviewing the volume of photos collected at our jobs without high tech assistance would be impossible. With Vinnie, we spend less time and get a much better picture of site safety. And all of our materials are organized, located and examined.”

    Hawaiian Dredging Construction Company

    “’s AI engine, Vinnie, has been trained to recognize construction risks in photos and other project data creating an unbiased, automated risk assessment that enables teams to have better visibility into risk.”