AI Inspection

Computer vision trained on fiber networks.

FiberQA's models are trained on thousands of FIST closures, splice cassettes and labeling configurations used by European fiber operators.

STEP 01

Upload Inspection Photos

Field crews capture closure, cassette, label and overview photos via the FiberQA mobile app or web upload.

STEP 02

AI Analysis

Vision models classify defects against your acceptance specification — labels, routing, slack, sealing and identification.

STEP 03

Quality Report Generated

Per-site score, geo-verified evidence and exportable PDF for client sign-off and contractor SLA tracking.

32 checks per closure, every time

Standardize what counts as a passing installation. Findings link directly to your acceptance specification so reports are defensible at sign-off.

  • Cassette label presence & legibility
  • Splice tray organization
  • Fiber slack within specification
  • Tube color order compliance
  • Closure sealing & gasket position
  • Identification label match (cabinet ID)
  • GPS metadata vs. work order
  • Cable entry strain relief
Inspection INS-2026-04812
Warning

Site

Antwerp North — Cabinet AN-247

Closure

FIST-GCO2-BC6 / Cassette 03

Technician

L. Janssen (Crew 14)

Captured

Jun 8, 2026 · 09:42 CET

51.2611° N, 4.4022° E (±2.1m)GPS verified

AI Findings

  • Cassette labels verified
  • Fiber routing compliant
  • GPS location verified
  • Excess fiber slack detected
  • Missing identification label
  • Tube organization requires correction
Quality Score
87/ 100

Estimated rework cost avoided

480

Photos

14

Checks

32

Bring AI inspection to your next acceptance milestone.