AI Table Extraction for Construction

Tables are everywhere in construction documents — door schedules, finish schedules, equipment lists, rebar schedules, concrete mix designs, test reports, and product data sheets. AI table extraction reads these tables and converts them into structured data that can be searched, compared, and analyzed.

The extraction challenge is that tables in construction documents are formatted for visual clarity, not data processing. They use merged cells, multi-line entries, abbreviated column headers, and references to other documents. A door schedule might have a column labeled "Hw Gp" (hardware group) with entries like "D" that reference a hardware specification section elsewhere in the documents. AI interprets these compressed formats and resolves the references.

Once extracted, tabular data supports automated workflows. AI compares the door schedule extracted from the drawings against the door schedule in the specification to verify consistency. It compares product data tables from submittals against specification requirements to check compliance. It aggregates quantities from schedules across all sheets to produce material takeoffs. Each of these workflows depends on accurate table extraction as the first step.