Projectr Analytics Information

Projectr develops machine learning solutions that structure construction project data so that teams can make better decisions. Project information is distributed across many entities, each with their own design, scheduling, cost, and document management systems. The reasoning behind decisions held in correspondence. Projectr extracts the objects and relationships contained in the data that project teams already produce and maintains them as a connected, current model of the project. The system integrates with existing AEC software rather than replacing it. A connected project model gives teams visibility into cost, schedule, quality, and safety that is normally only available after a problem has already occurred. Decisions, risks, and dependencies become traceable as the project happens, rather than reconstructed afterward. The result is a project team that can identify and act on issues earlier, with a clearer record of why decisions were made. Our work is grounded in applied research on construction document extraction, schema design, and graph analytics. Projectr is currently in research and development, with an emphasis on establishing a correct and durable data model before commercial release. This reflects our broader purpose: advancing the safe, responsible deployment of AI and next-generation technology in construction, an industry where errors carry real physical and financial consequences.