AI AutomationConstruction Tech / Trade Estimating

PlanTakeoff — Blueprint Estimating & Subcontractor Bid Engine

Domain / Scope
Commercial Electrical Subcontractor ($32M Commercial Tender Volume)
Year
2026
Duration
12 weeks
Primary metric
95% takeoff time reduction
45 mins
Average quantity takeoff time per 100-page plan set (reduced down from 16 hours)
2.8x
Increase in competitive commercial tender bids submitted per month
$4.1M
In new commercial contract awards won within first 6 months of deployment
98.7%
Symbol counting precision verified against master electrical legends
100%
Elimination of missed scope addenda during late-stage bid revisions
< 3 weeks
New estimator onboarding time required to run full commercial takeoffs

The Problem

System Bottlenecks & Technical Friction

A commercial electrical trade contractor bidding on NYC high-rise developments and healthcare facilities was bottlenecked by their manual estimating process. Senior estimators spent 14 to 20 hours per tender manually counting lighting fixtures, disconnect switches, and panel boards across 120+ page architectural and MEP PDF drawing sets in Bluebeam. Because bids had strict 10-day submission windows, the contractor had to pass on 70% of lucrative commercial RFPs simply due to lack of estimating bandwidth.

Our Engineering Approach

Architecture Design & Implementation

We engineered PlanTakeoff as an automated quantity takeoff platform purpose-built for commercial plan sets. The system ingests architectural vector PDFs, detects drawing scale bars automatically, and executes high-resolution computer vision inference to detect, classify, and count electrical symbols (switches, fixtures, receptacles, panels) against the sheet's specific symbol legend. A linear measurement engine calculates conduit and feeder run lengths along wall vectors. Estimators review the results in a web-based Canvas inspection UI with color-coded count overlays, adjust counts in seconds, and export structured bill of materials (BOM) directly into Excel or Procore.

Technical Architecture

System breakdown & stack.

8 core subsystem modules
01

Vector PDF layer parser extracting drawing title blocks, architectural scales, and layer metadata

02

Fine-tuned visual symbol detection model (PyTorch / OpenCV) trained on 22,000 electrical blueprint annotations

03

Automatic drawing scale detection calibrating pixel-to-foot ratios across architectural, structural, and MEP sheets

04

Linear vector measurement engine calculating wire run lengths with automated 10% waste buffer factors

05

Interactive HTML5 Canvas inspection UI rendering symbol bounding boxes and count heatmaps with 60 FPS zoom

06

Procore API and Excel BOM exporter generating itemized labor and material cost estimates with unit pricing formulas

07

PostgreSQL project database storing versioned plan sets and addendum delta comparisons

08

AWS S3 multi-tier image tile caching for seamless instant rendering of 200MB 300-DPI drawing sheets

PyTorchOpenCVFastAPIReactCanvas APIPostgreSQLAWS S3Procore API

Engagement Timeline

Engineering delivery schedule.

Total: 12 weeks
Weeks 1–2

Electrical blueprint dataset collection, symbol taxonomy mapping across standard CSI MasterFormat divisions

Weeks 3–6

PyTorch symbol detection model fine-tuning, scale calibration engine, vector extraction pipeline

Weeks 7–9

Linear conduit measurement engine, Procore API integration, Excel BOM generator

Weeks 10–11

HTML5 Canvas review UI, count validation tools, addendum visual diff engine

Week 12

Backtesting against 15 historical tender bids, estimator team training, full production rollout

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