AP Valletta, one of Malta’s foremost architecture and heritage conservation firms, faced a pressing need: how to efficiently monitor, document, and respond to deterioration across numerous historic sites. Given the country’s rich architectural legacy, ensuring timely maintenance and restoration is essential—but traditional methods were proving too slow and resource-intensive.
Site inspections required manual photo analysis, in-person surveys, and time-consuming CAD documentation, all prone to human oversight and inconsistency. As demand grew for scalable, accurate, and non-invasive methods to monitor degradation, AP Valletta looked for a digital solution that could bridge visual analysis with their architectural workflows—particularly AutoCAD.
The core challenge was to develop a tool that could automatically detect deterioration from photographs and map the findings onto architectural plans, saving valuable time while increasing precision in architectural diagnostics and restoration planning.
AI model trained on real deterioration cases from Maltese heritage sites
Detection of surface decay from standard photos (no special equipment needed)
Automated overlay of detected damage onto AutoCAD drawings, preserving scale
Generation of visual condition reports for use in planning, funding, and conservation
Cloud-based architecture, scalable for multiple sites and large image volumes
Neural AI developed a custom computer vision model trained to detect signs of deterioration—such as cracks, erosion, and staining—from standard site photos. The AI then automatically maps the damage onto AutoCAD drawings, providing architects with accurate, scaled visual data for immediate use. This eliminates manual analysis, reduces inspection time, and supports smarter planning and restoration. Built for scalability, the tool processes large volumes of imagery and generates condition reports, making it a powerful solution for AI-driven heritage conservation.
With LIMAP, we’re using AI and computer vision to give heritage conservation a digital upgrade—turning photos into actionable insights and AutoCAD-ready maps. It’s a game-changer for architectural preservation.
Matthew Galea - Neural AI's Managing Director
By automating the detection and mapping of damage, Neural AI helped AP Valletta scale their conservation work while protecting architectural integrity with data-driven precision.
Reduced manual image processing time by over 80%
Increased consistency and accuracy in deterioration reporting
Allowed non-invasive analysis of fragile historic structures
Seamless integration with AutoCAD, reducing documentation lag
Enabled smarter resource allocation across multiple heritage sites
