Comment Closure

Verified

Compares your review comment log against a submittal PDF and automatically classifies each comment with customizable verdicts such as resolved, not resolved, or investigate. Each comment is matched to the exact location on the drawing and flagged with a bounding box highlight, giving reviewers a direct path to the evidence without manually cross-referencing spreadsheets and drawings.

Comment Closure Overview

Comment Closure is an AI-powered submittal review tool that automatically compares a review comment log against a submittal PDF and classifies each comment with customizable verdicts such as resolved, not resolved, or investigate. It eliminates the manual process of cross-referencing spreadsheets against drawing sets, a task that typically takes reviewers hours or days on complex submittals, and replaces it with a structured, auditable AI verification in minutes.

The tool accepts two inputs: a comment source (either an XLSX comment log or an annotated PDF with native markup) and a submittal PDF. It parses every comment, extracting the comment number, description, sheet reference, discipline, and owner response, then matches each comment to its corresponding drawing sheet in the submittal. Matching uses a multi-strategy approach: exact drawing number lookup, fuzzy normalized matching, and AI embedding similarity search for comments that lack an explicit sheet reference. Comments that cannot be matched to any drawing are automatically flagged as Investigate so nothing falls through the cracks.

Once matched, a Claude Sonnet AI agent reads each drawing page and verifies whether the comment has been addressed, producing a verdict with a confidence level and a plain-language explanation of the evidence found. Compound comments containing multiple sub-requirements are automatically decomposed and each requirement is verified independently. Low-confidence verdicts are conservatively upgraded to Investigate to ensure ambiguous cases always receive human attention.

Every verdict is anchored to the exact location on the drawing where the evidence appears or is missing. The tool uses a multi-tier resolution strategy — including verbatim text search, vector index lookup, visual AI grounding, and PDF text search — to place a precise bounding box on the drawing page, giving reviewers a direct path to the evidence without having to hunt through the sheet manually.

Results are presented in a live review panel showing each comment's verdict, confidence score, explanation, and highlighted drawing location. An AI-generated executive summary identifies the most critical unresolved and investigate items by comment number, sheet, and page — giving project managers an instant action list. The full results export as an XLSX file with verdict for every comment, ready to share with the design team.

Comment Closure supports XLSX and XLS comment logs, annotated PDFs with native markup objects, multi-discipline submittals spanning architectural, structural, electrical, and mechanical sheets, and large comment sets with concurrent AI verification. A real-time progress feed streams each comment's verification as it happens, and runs can be cancelled at any point without data loss.

Comment Closure is an AI-powered submittal review tool that automatically compares a review comment log against a submittal PDF and classifies each comment with customizable verdicts such as resolved, not resolved, or investigate. It eliminates the manual process of cross-referencing spreadsheets against drawing sets, a task that typically takes reviewers hours or days on complex submittals, and replaces it with a structured, auditable AI verification in minutes.

The tool accepts two inputs: a comment source (either an XLSX comment log or an annotated PDF with native markup) and a submittal PDF. It parses every comment, extracting the comment number, description, sheet reference, discipline, and owner response, then matches each comment to its corresponding drawing sheet in the submittal. Matching uses a multi-strategy approach: exact drawing number lookup, fuzzy normalized matching, and AI embedding similarity search for comments that lack an explicit sheet reference. Comments that cannot be matched to any drawing are automatically flagged as Investigate so nothing falls through the cracks.

Once matched, a Claude Sonnet AI agent reads each drawing page and verifies whether the comment has been addressed, producing a verdict with a confidence level and a plain-language explanation of the evidence found. Compound comments containing multiple sub-requirements are automatically decomposed and each requirement is verified independently. Low-confidence verdicts are conservatively upgraded to Investigate to ensure ambiguous cases always receive human attention.

Every verdict is anchored to the exact location on the drawing where the evidence appears or is missing. The tool uses a multi-tier resolution strategy — including verbatim text search, vector index lookup, visual AI grounding, and PDF text search — to place a precise bounding box on the drawing page, giving reviewers a direct path to the evidence without having to hunt through the sheet manually.

Results are presented in a live review panel showing each comment's verdict, confidence score, explanation, and highlighted drawing location. An AI-generated executive summary identifies the most critical unresolved and investigate items by comment number, sheet, and page — giving project managers an instant action list. The full results export as an XLSX file with verdict for every comment, ready to share with the design team.

Comment Closure supports XLSX and XLS comment logs, annotated PDFs with native markup objects, multi-discipline submittals spanning architectural, structural, electrical, and mechanical sheets, and large comment sets with concurrent AI verification. A real-time progress feed streams each comment's verification as it happens, and runs can be cancelled at any point without data loss.

Company

Learn more about the company and team behind Comment Closure.

Structured AI

Structured is building the AI workforce for construction design engineering. Our platform automates QA/QC on engineering drawing sets, using cross-discipline vision-language agents.

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InspectMind AI

InspectMind is an AI-powered platform that reviews construction drawings, specifications, and submittals for potential code violations, coordination conflicts, constructability issues, and missing information. Designed for architects, engineers, contractors, owners, and municipalities, it provides evidence-backed findings that help teams complete plan checks and QA/QC more efficiently. By identifying costly issues earlier, InspectMind supports faster reviews, stronger documentation, reduced rework, and better-informed decisions throughout project planning and delivery across diverse project types.

Conformance

A subject-level checker for drawing sets that compares a submittal against a prototype (a reference set encoding the organization's brand or design standards).This collapses what is normally a slow, inconsistent manual review into a list of pre-located, pre-justified deviations, so reviewers spend their time accepting or rejecting findings instead of hunting for them.

Compare Versions

Takes two versions of the same drawing set and tells you exactly what changed between them, sheet by sheet. It surfaces specific MEP, architectural, and civil change. Each finding is tagged with discipline, severity, and confidence, with a box drawn around the exact spot on the page so reviewers can click straight to it. This tool is especially valuable for multi-discipline coordination and prototype or chain projects where the same set iterates many times.