AI intelligence system

CargoInspect

From inspection image to defensible damage evidence.

An automated container and cargo inspection system that captures condition at entry and exit, classifies damage consistently, and produces an evidence package that stands up in a claim.

Logistics Freight & Shipping Insurance Computer Vision Claims
Sector
Logistics, Freight & Insurance
Year
2024
Duration
6 months
Team
6 people
Platforms
Gate kiosk · Web · Mobile
Status
In production
CargoInspect — visual identity for the case study
6-face Capture coverage Every face, controlled geometry
Entry vs exit Comparison basis Custody delta, not opinion
Consistent Severity grading Independent of who is on shift
Claim-ready Evidence package Generated automatically

01 — The problem

Damage disputes were settled by argument. A container arrived damaged, the terminal said it arrived that way, the carrier said it did not, and the evidence was a handful of phone photographs taken from inconsistent angles by whoever was on the gate.

The inconsistency was the real cost. Two inspectors graded the same dent differently, so claims outcomes depended on who was working that shift rather than on the condition of the box.

02 — What we did

We standardised capture before touching classification. A fixed multi-camera portal photographs every face of every container under controlled geometry and lighting, so entry and exit images are directly comparable rather than approximately similar.

With comparable capture, difference becomes provable. The system aligns entry and exit imagery, isolates what changed during custody, and produces a package with both images, the delta, the classification and the full chain of custody attached.

You cannot prove a difference between two photographs taken from different angles.
Interface

What it looks like in use

Two of the screens that carry the most weight in daily use, rebuilt here from the production design system.

cargoinspect.aurezalabs.com/unit/MSKU4471882
MSKU 447188-2DELTA FOUND
Entry · 14 Mar 06:12 · grade B6 FACES
Exit · 19 Mar 17:48 · grade C6 FACES
Left panel · new deformation 340mmDURING CUSTODY
Repair estimate · code DP-3$1,140
Claim package generated

Difference becomes provableControlled capture geometry makes entry and exit images directly comparable, so what changed during custody is isolated rather than argued.

cargoinspect.aurezalabs.com/trends
Damage by handler · 90 daysCONSISTENT GRADING
Terminal 3 · door damage3.1x MEAN
Route AE-NL · corrosion1.2x MEAN
Findings per 1,000 moves

Patterns across the fleetConsistent grading made damage concentration by route and handler visible for the first time.

Capabilities

What the system does

Grouped by the job each set of capabilities exists to do, rather than by which team built it.

Capture

01 · Controlled by design

Multi-camera portal

Fixed camera array capturing every container face under consistent geometry and lighting as it passes the gate.

Identity capture

Container number and seal read automatically and reconciled against the booking.

Quality gating

Occlusion, motion blur and exposure problems detected at capture so the pass can be repeated immediately.

Mobile supplement

Inspectors add close-range detail shots that inherit the same metadata and chain of custody.

Assessment

02 · Consistent grading

Damage detection and segmentation

Dents, punctures, corrosion, door damage and structural deformation localised on the container surface model.

Severity assessment

Graded against the industry damage taxonomy so results are consistent across shifts and terminals.

Before and after comparison

Entry and exit imagery aligned to isolate exactly what changed during custody.

Repair estimation

Detected damage mapped onto standard repair codes and estimated cost.

Evidence and claims

03 · The commercial payoff

Report generation

Inspection reports produced automatically with annotated imagery and classification rationale.

Insurance evidence package

A complete bundle: both captures, the delta, grading, timestamps and custody chain.

Dispute support

Side-by-side presentation designed for a claims adjuster rather than an engineer.

Fleet condition trends

Damage patterns tracked by route, handler and equipment type.

Architecture

How it is put together

Layer by layer, with the reason each one exists — because the reason is usually the interesting part.

01Capture portal

Synchronised multi-camera rig with controlled lighting and trigger detection, producing a consistent capture set per pass.

  • Industrial cameras
  • Hardware trigger
  • Controlled lighting
02Identity resolution

OCR of container and seal numbers reconciled against terminal booking systems.

  • OCR
  • Terminal integration
03Damage models

Segmentation and classification trained against the industry damage taxonomy with calibrated severity output.

  • PyTorch
  • Segmentation
  • Taxonomy mapping
04Comparison

Geometric alignment of entry and exit captures with change isolation on the container surface model.

  • Image registration
  • Change detection
05Evidence service

Immutable storage of captures and findings with signed, exportable evidence bundles.

  • S3 object lock
  • Signed exports

Technology

Vision

  • PyTorch
  • Segmentation
  • Image registration
  • OCR

Hardware

  • Industrial cameras
  • Edge compute
  • Controlled lighting

Backend

  • Python
  • FastAPI
  • PostgreSQL
  • S3

Frontend

  • React
  • TypeScript
  • Annotation tooling
Outcome

What changed

Measured against how the operation ran before, not against a benchmark chosen after the fact.

  • Grading stopped depending on the shift. The same damage receives the same severity regardless of who is on the gate.

  • Custody deltas are provable. Controlled capture geometry makes entry-to-exit comparison meaningful.

  • Claims packages are automatic. Evidence bundles are generated from the inspection record, not assembled after a dispute.

  • Patterns emerged across the fleet. Damage concentrated by route and handler became visible for the first time.

How it ran

  1. Months 1-2

    Capture design

    Designed and validated the portal geometry, because comparability depends entirely on it.

  2. Month 3

    Identity and integration

    Container and seal OCR with terminal system reconciliation.

  3. Months 4-5

    Damage models

    Detection, taxonomy-aligned grading and entry-exit change isolation.

  4. Month 6

    Evidence and rollout

    Report generation, signed evidence bundles and gate deployment.

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