AI-Driven Cost Estimating

QTO Automation for Boutique Consultancies

AI-driven automation for construction and cost estimating, helping client streamline their workflows, improve accuracy, and enhance profitability.

Our solution enables teams to cut up to 50% of manual workload, reducing errors and improving project turnaround times.

Project Summary:

Project Summary:

For boutique consultancies, time is a crucial asset. Estimators and project managers spend countless hours manually scrubbing drawings, verifying scopes, and performing quantity takeoffs (QTO) in Bluebeam—tasks that are both labor-intensive and prone to human error.

At Lepei.pro, we specialize in AI-driven automation for construction and cost estimating, helping streamline their workflows, improve accuracy, and enhance profitability. Our solution enables teams to cut up to 50% of manual workload, reducing errors and improving project turnaround times.

For $10,000, we offer a pilot integration that allows to test AI-assisted QTO and drawing analysis within their existing workflow—delivering immediate cost savings and efficiency gains.


Faced Challenges:


Architectural blueprint of a building with intricate piping and structural details
Architectural blueprint of a building with intricate piping and structural details
Architectural blueprint of a building with intricate piping and structural details
1-Manual Drawing Scrubbing Slows Down Estimates

Problem: Estimators manually go through hundreds of pages of PDF drawings to locate MEP (mechanical, electrical, piping) elements, compare different revisions, and ensure all scopes are correctly accounted for.

Impact:
Time-intensive: This process adds 10–15 hours per project just for review.
High risk of missing scope changes, leading to costly change orders later.
Difficult to scale, client requires more clients.

2-Quantity Takeoff (QTO) in Bluebeam is 100% Manual

Problem: Estimators rely on manual measurement tools in Bluebeam to extract quantities for estimating.

Impact:
Slow process: Each project requires extensive clicking, measuring, and verification.
Inconsistent data: Human measurement errors lead to discrepancies.
Limited automation: Bluebeam’s default tools require manual calibration and selection.

3-Lack of AI-Powered Cost Forecasting

Problem: Client lacks a data-driven way to predict cost overruns based on historical project data.

Impact:
Difficult to anticipate material cost fluctuations.
More negotiation time spent defending estimates.
Limited insights on reducing waste or optimizing bids.

Lepei’s AI-Powered Solution:


AI-Driven Drawing Scrubbing

How It Works:
Our AI model scans PDFs, detecting MEP elements, scope discrepancies, and missing details.
It flags inconsistencies between different drawing revisions.
Generates a pre-analyzed PDF where critical changes are highlighted.

Technology Used:
YOLOv8 + Segment Anything (MEP object detection)
Tesseract OCR + AWS Textract (text extraction from PDFs)
Diffing Algorithms (automatic drawing comparison)

Benefits:
Saves 6–8 hours per project on drawing reviews.
Reduces scope omissions and costly mistakes.
Fully integrates with Bluebeam VisualSearch for manual refinement.

AI-Assisted Quantity Takeoff (QTO) in Bluebeam

How It Works:
AI detects cables, ducts, pipes, walls, and equipment in Bluebeam.
Generates automated takeoff reports with lengths, areas, and counts.
Outputs structured Excel/CSV files ready for estimating.

Technology Used:
OpenCV + Bluebeam API (Auto-detection of linework)
IfcOpenShell + Dynamo for Revit (For optional BIM workflows)
Excel/CSV integration for seamless export

Benefits:
Cuts manual takeoff time by 50%.
Ensures consistent, audit-ready QTO reports.
Works within Bluebeam, no need to switch software.

AI-Powered Cost Prediction & Forecasting

How It Works:
 Analyzes PC&A’s past projects to identify cost patterns.
Uses machine learning (XGBoost, Prophet) to predict overruns.
Outputs a dashboard with risk insights per project.

Technology Used:
XGBoost + Prophet (predictive analytics)
Google Sheets/Excel Plugin (for quick access)

Benefits:
Helps anticipate cost fluctuations early.
Improves client negotiations with stronger data.
Identifies historical cost trends for better estimating.

Implementation: Step-by-Step Roadmap

Implementation: Step-by-Step Roadmap

We provide a 4-week structured pilot program that lets client test and validate the AI workflow before a full-scale deployment.

Phase 1: Initial Setup (Week 1)

✔ Assess current QTO workflow.

✔ Define AI automation goals.

✔ Set up Bluebeam API + OpenCV for QTO detection.

Phase 2: AI Training & Calibration (Week 2)

✔ Train AI to recognize project-specific elements.

✔ Test MEP object detection on sample PDFs.

✔ Fine-tune auto-QTO generation in Bluebeam.

Phase 3: Live Testing (Week 3)

✔ Run AI-powered QTO on real projects.

✔ Compare manual vs. AI-generated results.

✔ Adjust system accuracy as needed.

Phase 4: Final Validation & Next Steps (Week 4)

✔ Deliver final AI-assisted QTO reports.

✔ Train team on how to use the system.

✔ Provide cost savings analysis & ROI breakdown.

Business Benefits:

Business Benefits:

ROI Breakdown

Current cost of manual QTO & drawing scrubbing:

• Estimator time: ~15 hours/project

• Hourly rate: ~$150

• Total wasted cost per project: $2,250

Projected AI time savings: 50%

Annual savings (20 projects/year): $45,000+

Investment: One-time $10,000 for setup → Pays for itself in <5 projects.

For more information on the technologies used, please follow the link

Let’s make estimating faster, smarter, and more accurate

Get In Touch

Get In Touch

Get In Touch