Automate Construction Project Schedules from Architectural Drawings

Most 30-person construction firms use Microsoft Project or Primavera P6 for project scheduling. These tools are powerful for managing a schedule once it exists, but they do nothing to help create it. They are blank canvases that require a project manager to manually read 50+ pages of drawings, identify every task, estimate its duration, and then type everything into the software, painstakingly linking each dependency.

Consider a project manager at a mid-sized general contractor who receives a 75-page drawing set for a new commercial build-out. They spend a full day with highlighters, cross-referencing architectural, structural, and MEP plans to build a master task list. They spend a second day entering these 200+ line items into Microsoft Project and linking predecessors. A single missed dependency, like ordering long-lead HVAC units after the framing is complete, can cause a cascade of delays that costs thousands in labor and penalties.

The structural problem is that the schedule logic is trapped in unstructured data, primarily visual drawings and text-based spec sheets. Software like PlanSwift can help with takeoffs, but its integration with scheduling tools is often a clumsy CSV export that loses critical context. Your scheduling software cannot 'read' the plans, so it relies entirely on a human to act as a slow, error-prone translation layer. This manual data entry is a non-billable administrative bottleneck that prevents experienced project managers from focusing on higher-value work.

The first step is to understand your specific scheduling logic. Syntora audits your past project schedules in MS Project or Primavera P6 to learn your typical task sequences, durations, and dependencies for different project types. We map out how you handle long-lead items, subcontractor coordination, and inspection milestones. This audit produces a 'scheduling playbook' that the AI will follow.

The technical system would use Gemini Pro to read architectural drawings and spec sheets, identifying tasks, zones, and material callouts. A Python script then maps these tasks into a dependency graph, applying the logic from your playbook. For instance, the system would learn that 'Install Rooftop HVAC Unit' must be preceded by 'Structural Steel Complete' and is a prerequisite for 'MEP Rough-in'. We would wrap this logic in a FastAPI service, processing a 50-page drawing set in under 5 minutes.

Syntora built a similar system for a commercial ceiling contractor to automate estimating, achieving 2-3% accuracy in under 60 seconds. For scheduling, the final output would be a pre-populated file for your existing software, like an .MPP for Microsoft Project. You receive a draft schedule with 80% of the manual work done, ready for your project manager to refine and finalize. You own the complete Python source code and the system runs on your cloud infrastructure for a hosting cost under $50 per month.