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Scan Analysis

Scan Analysis

Upload 3D scans, overlay your asset register, and let AI detect condition anomalies that improve over time.

Upload → Analyze → Review → Create Work Orders

Anomaly Queue & Work OrdersSeverity Heatmap
Frames: 8
Findings: 2
Pending: 0

Review findings in the anomaly queue, use Reassign Asset when needed, and create work orders from major or critical findings.

Review SLA Breach

3 overdue

3 pending findings past review SLA.

critical
0 / SLA 1d
major
1 / SLA 3d
moderate
0 / SLA 7d
minor
2 / SLA 14d
Browse scan gallery

Scans (4)

Uploaded
Frames (8)
AI analyzed (2)
Certified

Severity Heatmap

Select a scan frame to view its findings. Blue: minor, amber: moderate, orange: major, red: critical.

Selected scan evidence
Heatmap
dent

No.1 Grant Avenue — Lobby & Lift Bank, Q2 2026

GLB • 5 assets overlaid • 2 anomalies detected

Open 3D Scan Viewer

No 3D model available for this scan

Room tagging workspace

Link each JPEG frame to the Excel room list so AI findings and reports are grouped by room.

8/8 tagged
Front
Front
R01
Oblique-NE
Oblique-NE
R01
Right
Right
R01
Oblique-SE
Oblique-SE
R01
Rear
Rear
R01
Oblique-SW
Oblique-SW
R01
Left
Left
R01
Top-Down
Top-Down
R01

Confirm with Inspector Spreadsheet

Upload the condition spreadsheet for this scan. We match each row to the AI findings and show what's confirmed, AI-only, and sheet-only.

No spreadsheet uploaded yet.

Extracted LiDAR Frames (8)

Condition Over Time

No previous scans of this location to compare

Anomaly Queue

2
Review each highlighted asset photo, then click Verify, Fix AI, or Not issue. Or Log finding for defects you spot yourself.
0
Pending
1
Approved
0
Corrected
1
Rejected

Nothing in this filter.

Condition AI Model

Continuously learning from your feedback

Model Versionv3.2
Accuracy93.0%
Trained on
18400 samples
FP rate
0.1%
Pending training samples
1

Model performance

precision per version (from human review)
condition-grader-v4.1
71% · 7 reviewed

Precision = approved / (approved + corrected + rejected). Higher is better. Bump ai_model_version in analyzeScanCondition after prompt or model changes to see the impact here.