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MarkedUp

Automated QC and issue detection for construction drawings

AI-powered drawing audit platform that scans 2D PDF construction documents for missing callouts, broken references, door tag mismatches, and sheet index errors — delivering marked-up PDFs directly into Bluebeam, Autodesk, or Procore before errors reach the field.

Not publicly disclosed (backed by Mark Cuban) raisedEarly Stage
Founded 2024 · 100,000+ sheets audited; named clients include Titan AEC, Warren and Mahoney, Gordon Highlander, APDG Architects, MidHudson CM, AWIP
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WHY IT EXISTS

Why This Tool Exists

The Problem

Construction teams manually review 2D PDF drawing sets to catch missing callouts, mismatched door tags, and sheet coordination errors — a task that takes hours per cycle. Undetected drawing errors drive an estimated $65B/year in rework across US construction, with issues discovered only after procurement orders or subcontractor bids have been issued.

The Solution

Computer vision trained on 120,000+ AEC sheets automatically audits PDFs to flag broken callout references, door schedule mismatches, keynote-to-legend inconsistencies, and missing details — typically in seconds per page. Results export as standard marked-up PDFs that open directly in Bluebeam, Autodesk, or Procore without requiring any workflow change.

USAGE

How You Use It

Delivery Method
SaaSBluebeam IntegrationAutodesk IntegrationProcore Integration
Integrations
BluebeamAutodeskProcoreSharePointEagle Point Pinnacle Series
Disciplines
Architecture, Structural Engineering, Mep Engineering
Workflows
Design & BIM
Project Phases
Design Development, Construction Documents, Bidding
Project Types
Commercial, Healthcare, Residential, Hospitality
TRANSPARENCY

Data Transparency

Exactly what this tool uses and how

Input
What it needs
Required:2D PDF construction drawings
Optional:Project context information
Formats:PDF
Output
What you get
Format:Marked-up PDF with flagged issues
Fields:Missing callout references, Broken detail references, Door tag mismatches vs. door schedule, Keynote-to-legend inconsistencies, Sheet index alignment errors
Algorithm
How it works
Model:Proprietary computer vision (vector-native, AEC-trained) — model architecture not publicly disclosed; all processing on self-hosted infrastructure with no third-party AI providers
Accuracy:100,000+ sheets audited claimed (no independent accuracy metrics or false-positive rate published)
Privacy
How your data is protected
Retention:Uploaded PDFs and audit outputs automatically deleted after 14 days from production databases; backup deletion within 30 days; integration credentials purged within 48 hours of disconnection
Training:Customer data never used to train or fine-tune AI models; no customer drawings sent to third-party AI providers; all AI inference runs on self-hosted infrastructure
Compliance:AES-256 encryption at rest, TLS 1.2+ in transit, No SOC 2 or ISO 27001 certification (acknowledged in privacy policy), GDPR/CCPA for employee contact data only
API
Integration
Endpoint:Contact vendor for API access
Method:Not publicly documented
USE CASES

Use Cases

  • ·Pre-bid drawing audit to catch coordination errors before issuing to subcontractors
  • ·Construction documentation QC checkpoint during Design Development and CD phases
  • ·General contractor drawing review before sharing issued-for-construction sets
  • ·VDC/BIM manager automated quality gate for all issued drawing packages
  • ·Door schedule verification against architectural floor plans to prevent procurement errors
PRICING

Pricing

Free
First audit free (one-time risk-free trial with full refund guarantee)
Pro
On Demand: $1.25 per page (pay-as-you-go, 90-day storage)
Enterprise
Starting at $5,000/office/year — unlimited audits, custom rules, integrations, unlimited storage, Blueprint Academy access, analytics
Sources & Research NotesResearch date: 2026-07-08
Data Sources (7)
Fields Checked (17)
problem, solution, pricing, deliveryMethod, integrations, disciplines, projectPhases, projectTypes, yearFounded, privacy-retention, privacy-training, privacy-location, algorithm-approach, customerBase, vendor, website, domain
Not Found (7)
api-documentation, funding-amount, SOC2-certification, ISO27001-certification, exact-customer-count, accuracy-metrics, webhook-support
About this research: This record summarizes the cited sources and fields checked. A research date does not establish hands-on testing. Consult the original sources for current details and limitations.
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