What is Table Extraction AI?

AI for extracting structured data from tables in documents.

Table Extraction AI | AI for AEC Glossary | Nomic

Definition

Table Extraction AI automatically identifies and extracts structured data from tables in construction documents. These systems can parse door schedules, room finish schedules, equipment lists, and other tabular information from PDFs and drawings, converting them to structured data for analysis and verification.

In Depth

Table extraction reads structured data from tables in construction documents — door schedules, finish schedules, equipment lists, concrete mix designs, and product data tables. AI handles the variations in table formatting across different document types and sources, converting visual tables into structured data that can be searched, compared, and analyzed.

Examples

1

Extracting door schedules from drawings

2

Parsing finish schedules

3

Reading equipment schedules

Nomic Use Cases

See how Nomic applies this in production AEC workflows:

Automated Drawing Review

Automatically review drawings against building codes, internal standards, and client requirements.

Project Research

Instantly access all project-critical information from a single search interface.

All use cases Explore the platform

Frequently Asked Questions

Table Extraction AI automatically identifies and extracts structured data from tables in construction documents. These systems can parse door schedules, room finish schedules, equipment lists, and other tabular information from PDFs and drawings, converting them to structured data for analysis and verification.

Extracting door schedules from drawings. Parsing finish schedules. Reading equipment schedules.

Automated Drawing Review: Automatically review drawings against building codes, internal standards, and client requirements. Project Research: Instantly access all project-critical information from a single search interface.