SiteIntelligence combines computer vision, semantic AI, and large language models to give construction teams a real-time, objective view of site progress, document revisions, and visual anomalies.
Platform Modules
Each module targets a distinct stage of the construction and engineering lifecycle.
Upload pairs of weekly site photos and get a structured AI verdict on whether work is progressing, stable, or regressing. Uses semantic segmentation of 150+ site object classes, DINOv2 visual embeddings, and a two-agent LLM system for cross-validated scoring.
Upload two revisions of engineering drawings and instantly surface all design-significant changes. Detects only structurally meaningful differences using SHA-256 page hashing, then applies GPT vision to annotate each change with bounding boxes and metadata.
Build a reference image database and query it with any site photo to find visually similar captures ranked by AI similarity score. Supports user-submitted claims (e.g. "Added two scaffolds worth ₹5,000") which are verified by the LLM against both images.
Create and manage named reference image databases shared across modules. Embeddings are computed at upload time for instant query performance. View, tag, and browse all images in a database before using it in any analysis session.
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