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Contineu

AI-powered construction quality control with 360° defect detection

AI platform that uses helmet-mounted 360° cameras during site walks to automatically detect and track defects across all trades, creating visual defect mapping on floor plans with complete change history for streamlined QA/QC workflows.

$1.42M raisedEarly Stage
Founded 2023 · Tier I developers building residential projects in Mumbai, Bengaluru, Kolkata, and Delhi-NCR
Website →← All Tools
WHY IT EXISTS

Why This Tool Exists

The Problem

Construction quality control teams manually inspect every defect by hand, log issues through screenshots and messages, and chase down documentation across trades. This manual process takes site engineers 5+ hours daily and rework costs account for 5-7% of total project value, representing up to 50% of typical project profits.

The Solution

AI-powered platform uses helmet-mounted 360° cameras during routine site walks to automatically capture visual data, detect defects across all trades, and create structured QA/QC documentation with visual defect mapping pinned directly to floor plans and complete change history.

USAGE

How You Use It

Delivery Method
SaaSMobile App
Integrations
Not publicly documented
Disciplines
Architecture, Structural Engineering, Construction, Mep Engineering, Landscape Architecture, Civil Engineering
Workflows
Visualization & Presentation
Project Phases
Construction Administration
Project Types
Commercial, Residential, Mixed-Use, Healthcare, Education, Infrastructure, Industrial, Hospitality, Institutional
TRANSPARENCY

Data Transparency

Exactly what this tool uses and how

Input
What it needs
Required:360° site photos from helmet cameras, Floor plan layouts
Optional:Project schedule, Quality checklists, Historical defect data
Formats:360° images/video, CAD drawings, PDF plans, JPEG/PNG
Output
What you get
Format:Quality control dashboard with issue tracking
Fields:Defect detection and classification, Visual defect mapping on floor plans, Issue status and change history, Subcontractor performance metrics, Quality reports and analytics, Risk assessment and defect patterns
Algorithm
How it works
Model:Proprietary 3D computer vision models with construction-specific training
Accuracy:Claims to exceed state-of-the-art benchmarks on construction datasets (specific metrics not published)
Privacy
How your data is protected
Retention:Not publicly specified
Training:Not publicly specified
Compliance:Not publicly specified
API
Integration
Endpoint:Contact vendor for API access
Method:Not publicly documented
USE CASES

Use Cases

  • ·Automated daily site quality inspections
  • ·Defect tracking across multiple trades and locations
  • ·Subcontractor quality performance monitoring
  • ·Visual documentation for rework claims
  • ·Progress tracking with quality overlay
PRICING

Pricing

Free
Free trial available (less than 7 days)
Pro
Annual subscription (contact for pricing)
Enterprise
Custom pricing for enterprise deployments
Sources & Research NotesResearch date: 2026-02-01
Data Sources (5)
Fields Checked (8)
problem, solution, fundingTotal, yearFounded, customerBase, technology-approach, key-features, company-founders
Not Found (7)
pricing-details, api-documentation, privacy-policy, compliance-certifications, integrations, detailed-accuracy-metrics, data-retention-policy
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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