AI Damage Detection & Photo Triage
Help reviewers find the photographs that need attention.
Flag and organise possible visible damage so reviewers can focus on images that need attention.
The opportunity
The problem we help you solve
A large collection of asset, delivery or property images can contain useful evidence and a great deal of repetition. Opening every file to decide whether it needs investigation consumes time before the real assessment even begins.
Voxd helps evaluate a visual first pass that organises images and flags possible damage against agreed categories. We test representative examples and keep the source image attached to the finding. The aim is to support human triage with evidence, not to assume every visual judgement can be automated.
What changes for your team
Focus review effort
Help the team identify potentially relevant images within a larger collection.
Make findings easier to inspect
Keep the original photograph available so a reviewer can understand and check the result.
Use consistent categories
Agree what the system should flag and how uncertain or difficult cases are handled.
What we deliver
What Voxd can deliver
Inspection definition
Set damage categories, review priorities and the consequences of missed or false detections.
Feasibility evaluation
Test representative normal, damaged and difficult images against agreed criteria.
Review workflow
Connect findings to a suitable queue or operational record where people can act.
Why Voxd
A practical route from detection to an operational tool.
Voxd brings AI development, workflow automation and custom software together. We can build the review interface, connect the result to an existing system and design how uncertain cases reach a person.
We begin with feasibility because different visual tasks have very different requirements. You get a way to test the opportunity before committing to a larger deployment, with a decision based on your images and operating conditions.
How we work
Prove it in your environment
- 01
Define the inspection
We agree what should be detected, what acceptable variation looks like and the practical consequences of a missed detection or false alarm.
- 02
Assess representative images
We review camera setup, image quality and examples of both normal and difficult conditions. Gaps in the sample are identified early.
- 03
Run a measured pilot
We evaluate detection quality and the review workload against agreed criteria, including examples outside the easiest cases.
- 04
Connect useful results
If the pilot supports proceeding, we integrate the findings into a working process with human review, ownership and ongoing performance checks.
Before you get started
Before you get started
Can it decide liability or repair cost?
Those are separate decisions requiring appropriate evidence and expertise. The starting scope is visual detection and triage, not an assumed commercial conclusion.
Can you use photographs taken on phones?
Possibly. We assess viewpoint, image quality and variation before deciding whether the collection can support the task.
Find out whether a visual first pass would help your team.
Bring representative photographs and explain what reviewers need to spot.