Automate Your Bid Preparation and Win More Projects

Many construction companies and specialty contractors still face significant bottlenecks in their pre-construction workflows. Estimators often spend their days flipping through 50+ pages of architectural drawings per project, manually extracting quantities from takeoff software like PlanSwift, and then re-keying that data into complex Excel pricing engines. This manual transfer between systems is not just slow—taking 1-8 hours for each takeoff—but is also a common source of costly errors.

Consider a scenario where three estimators are trying to manage 30 or more takeoffs per week. This volume creates a scaling bottleneck, limiting your bidding capacity and growth. Missed scope items, especially critical details like 'typical floor' labels (e.g., floors 2-17 are identical), can lead to catastrophic square footage undercounts if overlooked manually, forcing your company to stand behind a quote that doesn't cover actual costs.

The problem compounds when dealing with subcontractor quotes. Responses arrive in wildly varied formats—single-page PDFs, multi-page Word documents, or just email bodies. Your estimators then have to meticulously find, compare, and transfer every line item, material code, quantity, and unit price into your master Excel sheet. This process is ripe for errors, where a single misplaced decimal can erase an entire project's profit margin.

Existing project management platforms, from Procore to Autodesk Construction Cloud, while excellent for post-award project execution and document storage, often fall short during the pre-bid phase. They are designed as systems of record, not systems of intelligence. These platforms typically lack the capability to intelligently read a subcontractor's PDF, identify a specific furnace model number, and normalize its price and specifications against other bids from different trades. Similarly, accounting systems like QuickBooks handle the financial record-keeping but offer little help in the granular data extraction and comparison needed for accurate bidding. The critical pricing and scope data remains trapped within unstructured documents, hindering your ability to bid more accurately and efficiently.

Syntora approaches pre-construction automation as a tailored engineering engagement, focusing first on understanding your specific workflows and existing tools. The initial step is a detailed discovery phase, where we audit your typical bid documents, architectural drawings (like reflected ceiling plans and floor plans), and subcontractor quotes. This audit identifies common document structures, the critical data points you need to extract—such as material quantities, ceiling types, zone measurements, or specific product specifications—and defines a precise data schema. This process also determines which existing pricing engines in your Excel templates need to be preserved and and how they auto-recalculate.

Building on our experience, where we deployed a system that reads architectural drawings using Gemini Vision with a dual-pipeline approach, we design a similar pattern for your specific needs. For drawing analysis, we would utilize Gemini Vision for specialized plans or Gemini Pro for broader plan types, employing both vision-only and OCR-assisted pipelines to extract data like material types and quantities. For deterministic calculations, such as grid layouts or seismic requirements in ceiling systems, Python applies auditable formulas, ensuring repeatable and accurate results. A 5-pass verification pipeline with outlier trimming, as deployed in our previous work, would ensure accuracy within 2-3% of manual takeoffs, consistently processing projects in under 60 seconds.

The extracted data is then structured for direct integration into your estimation workflow. We would automate Excel population via openpyxl, scanning column A labels to precisely locate quantity cells and ensuring all your embedded pricing formulas remain intact for automatic recalculation. The custom system would be built using Python and FastAPI for the core logic and API, potentially leveraging Supabase for secure data storage and real-time processing, depending on your scale and requirements.

The delivered solution would be a custom pipeline that connects directly to your existing systems. This includes pulling documents from Google Workspace, integrating with takeoff software like PlanSwift for validation, populating your Excel pricing engines, and potentially syncing final bid data with accounting systems like QuickBooks. Our engagement concludes with the delivery of the full Python source code, a comprehensive runbook for maintenance and operations, and guidance on hosting, ensuring you retain full ownership and control over the automation.