Conformance

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.

Key Facts

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Tool Overview

The Conformance Tool is an AI-powered drawing review platform that automates the comparison of architectural and engineering submittal drawings against an organization's prototype or standard reference set. Built for firms that enforce consistent design standards across a portfolio of built projects — including hotel brands, retail chains, restaurant franchises, healthcare networks, and multi-site corporate tenants — the tool transforms what is traditionally a slow, manual, and inconsistent review process into a structured, evidence-backed audit trail.

At its core, the Conformance Tool ingests two PDF drawing sets: a prototype (the company's reference standard encoding brand, design, and technical requirements) and a submittal (the drawings produced by an architect, contractor, or franchisee for a specific project). The system then executes a multi-pass analysis pipeline. First, it pairs sheets between the two documents by drawing number, classifying each pair as matched, modified, unchanged, added, or removed. Within each matched pair, the tool extracts discrete drawing subjects — floor plans, elevations, sections, and details — and matches them across the prototype and submittal, flagging any subject that is missing from the submittal or appears as an unexpected addition. A secondary pair-swap audit re-validates same-category subject clusters to catch crossed matches between, for example, two adjacent elevations.

Once subjects are aligned, the tool runs structured change detection to surface MEP and architectural deviations within each matched subject. Every finding is captured with category, severity, confidence score, element type, description, and pixel-accurate bounding boxes on both drawings — so reviewers can see exactly where on each sheet the deviation occurs. An ensemble approach runs the detection across three independent AI drafts; findings flagged by all three are surfaced as high-confidence core issues, while single-draft findings are routed to a long-tail review queue, giving reviewers built-in triage prioritization.

Each finding is then linked on demand to the specific prototype criteria note that establishes the requirement being violated, providing instant justification without manual cross-referencing. The platform also extracts callout annotations (numbered markers and their referenced notes) from prototype drawings, persisting them with spatial coordinates for overlay rendering.

Reviewers navigate findings through multiple lenses: by sheet pair, by subject, by room (using extracted room metadata), or by discipline. The tool delivers a comprehensive structured report summarizing matched, modified, added, and removed sheets, broken down by discipline, with full pair-level detail. Real-time progress streaming, soft-delete with worker cancellation, and tenant-scoped access controls round out the production-grade infrastructure. The result: senior reviewers shift from hunting for deviations across hundreds of sheets to efficiently accepting or rejecting a pre-located, pre-justified list of findings — dramatically reducing review cycles while improving consistency across projects.

Pricing

Free Trial

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Supported Project Type
Ideal for Company Size

Company Info

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Company Name
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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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