AI OCR for Construction Documents

OCR for construction documents goes beyond standard character recognition because construction documents contain a unique mix of text styles, orientations, and contexts that general-purpose OCR systems handle poorly. Dimension text runs along dimension lines at various angles, keynote text is small and densely packed, and title block text uses specific fonts and formatting.

AI-enhanced construction OCR is trained to recognize the specific patterns found in AEC documents. It reads dimension strings and understands the format (feet-inches-fractions), interprets keynote numbers and connects them to legends, reads room names and numbers within room boundaries, and extracts the structured text from title blocks. The accuracy improvement over generic OCR is substantial — from roughly 85-90% for general OCR to 95%+ for specialized construction OCR.

Handwritten annotations present an additional challenge. Field markups, as-built notations, and review comments are often handwritten on printed drawings. AI OCR trained on construction handwriting can recognize common annotations — "VERIFY IN FIELD," "SEE RFI #42," "ADDED PER ASI #7" — and convert them to searchable text. This makes the markup history of a drawing set accessible for future reference, which is valuable during claims analysis and project closeout.