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Oracle Construction Intelligence Cloud (formerly Newmetrix)

AI-powered jobsite safety monitoring and hazard detection

Computer vision platform that automatically analyzes jobsite photos and videos to detect safety hazards, track compliance, and predict incidents. Part of Oracle Construction Intelligence Cloud.

$22.4M raisedEstablished
Founded 2015 · Major contractors including JE Dunn, Shawmut Design and Construction, Warfel, Barton Malow, Suffolk, Obayashi, Lithko
Website →← All Tools
WHY IT EXISTS

Why This Tool Exists

The Problem

Construction teams manually review hundreds of daily jobsite photos to identify safety hazards, a process that takes hours and often misses issues. Safety incidents cause project delays, increased insurance costs, and worker injuries—often costing contractors hundreds of thousands per incident.

The Solution

Newmetrix automatically analyzes jobsite photos and videos with computer vision trained on 12 centuries of incident data and 17 million construction images. Its AI engine (Vinnie) detects 100+ safety hazards and predicts which projects are at highest risk within minutes, enabling preventive action.

USAGE

How You Use It

Delivery Method
SaaSMobile App
Integrations
ProcoreAutodesk BIM360Oracle AconexOxBlueBoxEgnyteSharePoint Online
Disciplines
Construction
Workflows
Data & Automation
Project Phases
Construction Administration
Project Types
Commercial, Infrastructure, Mixed-Use, Industrial, Hospitality
TRANSPARENCY

Data Transparency

Exactly what this tool uses and how

Input
What it needs
Required:Jobsite photos or videos, Project information
Optional:Procore project data, BIM 360 documents, Project schedule
Formats:JPG, PNG, MP4, Video streams, Mobile photos
Output
What you get
Format:Safety risk assessments and analytics dashboards
Fields:Detected hazards with severity ratings, Safety compliance scores, Risk predictions by project, Incident trend analysis, Worker safety benchmarking, Corrective action recommendations
Algorithm
How it works
Model:Proprietary computer vision AI trained on construction safety incidents
Accuracy:Trained on 12 centuries of incident data and 17 million construction images; can detect 100+ safety hazard types (specific accuracy metrics not publicly specified)
Privacy
How your data is protected
Retention:Photos and videos retained according to project lifecycle (specific retention period not publicly specified)
Training:Not publicly specified whether photos are used for AI model retraining
Compliance:SOC 2 (inferred from Oracle enterprise standards), GDPR (likely, as part of Oracle portfolio)
API
Integration
Endpoint:https://api.smartvid.io/api/v1/doc (documented in help center)
Method:REST API (POST for authentication, GET/POST for integration operations)
USE CASES

Use Cases

  • ·Automated daily jobsite safety inspections across multiple projects
  • ·Identify and correct PPE compliance issues before incidents occur
  • ·Detect workers at height, scaffolding, and fall risks automatically
  • ·Benchmark safety performance across project portfolio
  • ·Predict high-risk projects and allocate safety resources proactively
  • ·Create objective safety records for insurance and liability protection
PRICING

Pricing

Free
Not publicly available
Pro
Contact vendor for pricing (likely project-based or per-photo analysis)
Enterprise
Custom pricing as part of Oracle Construction Intelligence Cloud
Sources & Research NotesResearch date: 2026-02-01
Data Sources (10)
Fields Checked (21)
vendor, website, yearFounded, maturityStage, customerBase, fundingTotal, problem, solution, deliveryMethod, integrations, disciplines, projectPhases, projectTypes, input-required, input-optional, input-formats, output-format, output-fields, algorithm-approach, control-features, use-cases
Not Found (7)
pricing-details, detailed-privacy-policy, data-retention-specific-duration, soc2-certification-report, model-accuracy-quantified-metrics, api-rate-limits, data-training-practices
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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