Scalable PDF Rendering Infrastructure Upgrade for Digital Construction Estimating Platform

This project involves upgrading the PDF rendering infrastructure for Quantify, a digital construction estimating platform. The current in-house PDF engine was originally designed for AI training purposes and lacks the features, performance, and scalability required for displaying construction drawings and specifications in a cloud-based environment.
The existing system has significant limitations including missing critical functionality such as drawing overlays (essential for construction workflows), unreliable measurement tools, frequent rendering failures, and an unmaintainable codebase that prevents the addition of new features. These technical constraints have directly impacted client satisfaction and the platform’s ability to scale.
The project will replace the legacy system with Nutrient, a commercially supported, PDF specification-compliant rendering engine. The intern will be responsible for integrating and modifying the Nutrient SDK to work within Quantify’s architecture, including code customization, rigorous testing across various construction document types, and developing new features to achieve feature parity with the current engine while extending capabilities beyond existing limitations. This upgrade will deliver improved performance, enhanced reliability, and comprehensive feature capabilities necessary for professional construction document processing. The new solution will provide robust measurement tools, drawing overlay functionality, and a stable foundation for future feature development.

Faculty Supervisor:

Md Moniruzzaman

Student:

Partner:

Patabid Inc.

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Thompson Rivers University

Program: