AI Quantity Takeoff Platform Case Study

Client Overview

The client operates in the construction and estimation domain, where speed, accuracy, and data confidentiality are critical to project success. With large engineering drawings and complex blueprints forming the core of their workflow, manual quantity takeoff had become a bottleneck, slowing teams down and increasing the risk of costly errors. They partnered with Akoode Technologies to build a robust AI-powered solution that could modernize estimation workflows while keeping sensitive project data fully secure and under their control.

Country

Canada

Industry

Construction & Real Estate

Services Used

Artificial IntelligenceComputer Vision TechnologyEnd-to-End Tailored SoftwareEnterprise Application Development

Case Study - AI Quantity Takeoff

How Akoode Technologies Transformed a Manual Estimation Process Into an Ai-Driven Product

The client needed a production-ready AI application that could integrate seamlessly into existing estimation workflows without disrupting existing processes or requiring cloud dependency.

A desktop-based solution compatible with Windows, macOS, and Linux.
Automated material and fixture detection from architectural and engineering drawings.
Ability to process large, high-resolution PDFs without loss of detail.
Offline AI processing to ensure complete data privacy.
Interactive controls for manual review, adjustments, and pricing.
Professional exportable reports for downstream cost estimation.

Our Process

Our Approach to Building an AI-Powered Estimation System

A performance-focused approach designed to automate quantity takeoff from complex blueprints while ensuring accuracy, scalability, and complete data privacy.

Workflow & Blueprint Analysis

We analyzed estimation workflows and blueprint structures to identify inefficiencies in manual counting and reporting.

Object Detection Model Development

We implemented and optimized YOLO-based models to detect architectural elements such as doors, windows, fixtures, and utilities.

High-Resolution Processing Optimization

We integrated slicing techniques (SAHI) to process large-format drawings without losing detail or detection accuracy.

Desktop Application & System Integration

We built a cross-platform desktop application combining a responsive UI with a local AI backend for seamless, offline operation.

Workflow & Blueprint Analysis

We analyzed estimation workflows and blueprint structures to identify inefficiencies in manual counting and reporting.

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Challenges We Faced

Processing large, high-resolution engineering drawings accurately while maintaining speed, preventing detection errors, and ensuring complete data privacy through offline execution.