Comment Closure

Comment Closure

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.

Key Facts

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Tool 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.

Pricing

Free Trial

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Supported Project Type
Ideal for Company Size

Company Info

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About the Company

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. Every finding is returned deterministically with the exact page, location, rule, and fix. Our agents review drawing sets against code, spec, and firm standards in 30 minutes solving the QA/QC bottleneck behind $177B in annual rework. Structured AI deploys vision-language agents that review every set against code, spec, and firm standards in 30 minutes, turning a weeks of monotonous work into a frictionless QA/QC gate. The platform combines vision-language models with OCR to parse drawings and identify symbolic and image-based elements (MEP symbols, structural callouts, annotations), a multi-agent review system that runs cross-discipline checks in parallel, and internal fine-tuned LLMs for natural-language reasoning over codes, specs, and firm standards. A built-in chatbot copilot handles software navigation and onboarding for a frictionless user experience. 70% of construction rework starts with errors in design drawings. Structured AI deploys vision-language agents that review every set against code, spec, and firm standards in minutes through a frictionless QA/QC gate, solving a 177bn rework problem. Our vision is an AECO industry where design errors no longer reach the field, where the tacit expertise engineers is translated to every project on earth. The documents that govern the built environment become a verified, defensible source of truth. The billion-dollar tax that rework imposes on construction goes to zero. Our competitive advantage is years of domain expertise, compounded with elite commercial talent. Our CTO has spent nearly a decade building AI for the AEC industry, scouted at 18 to build innovation tools for Syska Hennessy Group. We've compounded this depth as we've scaled. Our engineering hires include software engineers with direct mechanical and electrical engineering experience, and architects. People who have stood on jobsites and reviewed drawings themselves. Our team understands the customer because, in many cases, our team has been the customer. Structured AI is built on agentic AI throughout the stack: vision-language models with integrated OCR parse engineering drawings and recognise symbolic, image-based, and tabular elements; a multi-agent design-review system runs code, coordination, spec, and standards checks concurrently; proprietary fine-tuned LLMs reason over project documentation with engineering-grade accuracy; and a natural-language chatbot provides in-product navigation and contextual onboarding — so the entire experience, from review to interrogation, runs on emerging AI technology. We’d love to work with architecture and engineering firms across MEP, structural, civil, and architectural disciplines: the teams that author the drawing sets every building, road, and piece of infrastructure is built from. We’d love to hear from design engineers, QA/QC managers, engineering directors, and principals: the people responsible for ensuring drawing sets are accurate, code-compliant, and aligned with firm standards before issuance. We serve the full size spectrum, from boutique multi-disciplinary studios to enterprise AE firms producing thousands of sheets per month. We also love to work with general contractors and owners who inherit these drawings downstream who feel the same pain (RFIs, change orders, rework) and benefit directly when the upstream QA layer is automated.
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. Every finding is returned deterministically with the exact page, location, rule, and fix. Our agents review drawing sets against code, spec, and firm standards in 30 minutes solving the QA/QC bottleneck behind $177B in annual rework. Structured AI deploys vision-language agents that review every set against code, spec, and firm standards in 30 minutes, turning a weeks of monotonous work into a frictionless QA/QC gate. The platform combines vision-language models with OCR to parse drawings and identify symbolic and image-based elements (MEP symbols, structural callouts, annotations), a multi-agent review system that runs cross-discipline checks in parallel, and internal fine-tuned LLMs for natural-language reasoning over codes, specs, and firm standards. A built-in chatbot copilot handles software navigation and onboarding for a frictionless user experience. 70% of construction rework starts with errors in design drawings. Structured AI deploys vision-language agents that review every set against code, spec, and firm standards in minutes through a frictionless QA/QC gate, solving a 177bn rework problem. Our vision is an AECO industry where design errors no longer reach the field, where the tacit expertise engineers is translated to every project on earth. The documents that govern the built environment become a verified, defensible source of truth. The billion-dollar tax that rework imposes on construction goes to zero. Our competitive advantage is years of domain expertise, compounded with elite commercial talent. Our CTO has spent nearly a decade building AI for the AEC industry, scouted at 18 to build innovation tools for Syska Hennessy Group. We've compounded this depth as we've scaled. Our engineering hires include software engineers with direct mechanical and electrical engineering experience, and architects. People who have stood on jobsites and reviewed drawings themselves. Our team understands the customer because, in many cases, our team has been the customer. Structured AI is built on agentic AI throughout the stack: vision-language models with integrated OCR parse engineering drawings and recognise symbolic, image-based, and tabular elements; a multi-agent design-review system runs code, coordination, spec, and standards checks concurrently; proprietary fine-tuned LLMs reason over project documentation with engineering-grade accuracy; and a natural-language chatbot provides in-product navigation and contextual onboarding — so the entire experience, from review to interrogation, runs on emerging AI technology. We’d love to work with architecture and engineering firms across MEP, structural, civil, and architectural disciplines: the teams that author the drawing sets every building, road, and piece of infrastructure is built from. We’d love to hear from design engineers, QA/QC managers, engineering directors, and principals: the people responsible for ensuring drawing sets are accurate, code-compliant, and aligned with firm standards before issuance. We serve the full size spectrum, from boutique multi-disciplinary studios to enterprise AE firms producing thousands of sheets per month. We also love to work with general contractors and owners who inherit these drawings downstream who feel the same pain (RFIs, change orders, rework) and benefit directly when the upstream QA layer is automated.

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