About VisionInspect.AI
We build custom computer vision models for one job at a time. No platform to learn, no annotation team to hire, no MLOps to figure out. You send photos, we deliver an API that returns structured detections.
Why we exist
Most teams that need vision in their inspection workflow don't need another self-serve SaaS. They need somebody who will look at their actual photos, tell them what's reliably catchable, and ship a working endpoint. The annotation tooling, synthetic data generation, training infrastructure, and monitoring stack are ours; the model trained on top is yours.
Damage detection is where this work began. Cargo and loading-dock documentation is the natural extension: the gap between "we took photos" and "we have a defensible record for the dispute file" is large, painful, and quantifiable. The same platform handles manufacturing defects, vehicle damage, PPE compliance, and the other use cases listed on our use cases page, but cargo is where our first paid builds are landing.
How we work
Targets in writing
Precision and recall numbers in your SOW, in your language, before any build work begins.
Walk-away clause
If V1 misses the targets, you keep the discovery deliverables and owe nothing further. No termination fee.
One person owns it
You talk to the person doing the work. No account managers, no handoffs, no week-long email loops.
Who runs this
VisionInspect.AI is a small operation, run by Jeremy Martin out of Massachusetts. We came to AI through damage detection, not the other way around. That shaped how the platform is built: every part of the stack, from the annotator to the synthetic data generator to the training pipeline, exists because a real damage-detection build needed it. The work is hands-on. I run the discovery calls, look at the photos, set the targets, and ship the model.
If you want to talk through whether your workflow is a fit, the fastest path is to send 20 to 50 photos through the free feasibility check. You'll get a one-page report with no follow-up unless you ask for one.
What this is not
- Not a self-serve labeling platform you log into and figure out yourself.
- Not a generic foundation model you wrap with a prompt.
- Not an offshore labeling shop. Annotation is part of the build, not the product.
- Not a research demo. Every deliverable is something you can put in a dispute file or a TMS.
Send 20 to 50 photos for a free feasibility check
One-page report on what's reliably catchable today, what's hard, and what a custom build would unlock. No commitment.
Free assessment