CASE STUDY · CONSTRUCTION AI
Turning construction drawings into structured, usable data.
Construction drawings contain valuable project information, but extracting it manually can be time-consuming. This project explores how computer vision and OCR can help turn complex drawings into structured information.
PROJECT OVERVIEW
- INDUSTRY
- Construction
- PROJECT TYPE
- AI-powered software workflow
- STAGE
- Working MVP
- CAPABILITIES
- Computer Vision, OCR, AI-Assisted Drawing Analysis, Structured Data Extraction
01 · THE CHALLENGE
Valuable data, locked inside drawings.
Construction and engineering drawings carry a large amount of project information: dimensions, annotations, symbols, labels and notes, often spread across many dense sheets.
When teams need that information for estimation, planning or reporting, someone usually has to read it off the drawings by hand and re-enter it elsewhere. The work is slow and repetitive, and every manual step is a chance for something to be missed or mistyped.
The goal was to find out whether AI could locate the relevant parts of a drawing, read them, and turn them into structured data that other tools and people can work with.
02 · THE SOLUTION
An AI-assisted workflow, from drawing to data.
We built a workflow that takes a drawing through six stages, each one turning visual information into something more structured and useful.
- 01
Drawing analysis
Drawings are uploaded and analysed to understand their layout and content.
- 02
Visual-region detection
Computer vision locates the regions of each drawing that hold relevant information.
- 03
OCR-based extraction
Text and values inside those regions are read automatically with OCR.
- 04
Structured information processing
Extracted data is organised into a consistent, structured format.
- 05
Quantity-estimation support
The structured data supports quantity estimation, ready for the team to review.
- 06
Dashboard and data export
Results are managed in a project dashboard and exported in multiple formats.
03 · KEY CAPABILITIES
What the platform does.
Drawing analysis
Analyses construction and engineering drawings and detects the visual regions that matter.
OCR and information extraction
Reads text and values from drawings automatically, instead of typing them in by hand.
Structured data processing
Organises extracted information into a structured format other tools and people can use.
Quantity-estimation support
Uses the structured data to support quantity estimation. Estimates are a starting point for professional review, not a replacement for it.
Project dashboard
Keeps projects and their drawings in one place, with user management for the team.
Data export
Exports results in multiple formats so the data can move into existing tools.
04 · TECHNOLOGY
Built with
- AI
- Computer vision, OCR
- Backend
- Python, FastAPI
- Frontend
- React
- Data
- PostgreSQL
- Infrastructure
- AWS, Docker
05 · OUTCOME
A working MVP that proves the approach.
The project delivered a working MVP. It showed that drawing analysis, OCR and computer vision can work together inside a practical software workflow, taking a drawing all the way to structured, exportable data.
It gives construction teams a foundation for reducing manual drawing review, while keeping people in control of the final numbers.
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