Buildots, which uses AI and computer vision to modernize construction management, announced scheduling integrations that will feed data directly from construction sites to planning platforms, automating the process by which teams update and understand progress.
Construction teams depend on project planning platforms like Oracle Primavera P6, Asta Powerproject and Microsoft Project, which require manual input to update progress and schedules. This means that site teams regularly and manually compile progress reports - a laborious and time-consuming process. Beyond gathering information from unaligned sources, it often requires referring back to building sites to double and triple check gathered information.
Buildots provides a single source of truth for construction site activities. By collecting data with hardhat-mounted 360° cameras and processing this data with AI, its solution enables teams to keep construction on schedule and flag mistakes in real time. Buildots' new integrations create a direct sync between on-site activities and project planning platforms. This provides teams with coherent information in real time, enabling them to understand progress and better predict when projects will end.
By feeding data directly to planning platforms, these integrations automate real-time progress into scheduling, enabling schedule owners to allocate more time to decision-making instead of organizing and sifting through data collected from sites.
"After seeing our clients manually updating their schedules based on the data provided by our platform, we immediately saw the potential for freeing up managers' precious time on site, The highly accurate data that is now automatically fed into schedules will help planners provide better estimates and respond more quickly to developments affecting their projects."
Roy Danon, co-founder and CEO of Buildots
Buildots is a Tel Aviv and London-based startup leveraging the power of AI and computer vision to modernize the construction management industry. Buildots uses hardhat-mounted cameras to capture imaging of every detail of an ongoing project during regular site walks. The data is then analyzed using AI models to transform random visual data into highly accurate, actionable insights that are correlated with the project's designs and schedule.