What we need to see
Your inspection checklist, representative images and labelled examples of acceptable parts and known defects.
AI work pattern · every industry
Spot the Defect Before It Leaves the Bay.
You don't need a million-pound machine-vision rig to catch quality issues. A modern AI model running on a phone or a £400 fixed camera can spot missing welds, wrong components, surface defects, and assembly errors, instantly, consistently, on every part. We build the pipeline that turns your existing photos into a quality safety net.
Tell us the task, your current tools and where the work gets stuck. We will help you choose a sensible first scope.
Prove it on your own work first.
How we judge the pilot
Measure missed defects and false alarms by defect type under real lighting and camera conditions.
What stays in your hands
Your quality lead decides what can pass. Physical measurements, safety checks and final release remain with qualified staff.
The work in context · Illustrative scenes
Map the inputs and the handovers.
Start with representative examples, the tools involved and the point where the work slows down.
Make review part of the workflow.
Show the prepared work to the right person, flag uncertainty and keep a clear route to correct mistakes.
The problem, in plain English.
01
QC is the most boring job in the building
Eyeballing 300 identical parts for the one with a missing weld is exactly the work humans are worst at. Attention drifts. Defects slip through. Costs end up on your warranty bill, not your QC line.
02
The good QC person leaves
Quality control depends on experience, knowing what to look for, what "normal" looks like for this product. When that person retires, quality dips for six months while you train the next one.
03
Customers want photo evidence anyway
Modern B2B customers ask for pre-dispatch photos. You're already taking them. You're not yet using them to actually inspect, they're just sitting on someone's phone.
04
Off-the-shelf machine vision is overkill
Industrial vision systems are £20k+ per station and assume a production line that runs the same product all day. For SMEs with varied work, that maths never works.
What actually happens.
01
Define what "right" looks like
A handful of reference photos and a written checklist per product type. We translate that into a structured inspection schema the AI can apply consistently.
02
Capture however you already capture
Phone, fixed camera, drone shot of a roof, scanner output. The same model handles any image source. No specialist hardware in 90% of cases.
03
Inspect against the schema
For each photo: pass/fail per criterion, with reasoning. Missing weld? Flagged. Wrong colour finish? Flagged. Damaged corner? Flagged. Clean? Through to dispatch with a confidence score.
04
Build an audit trail
Every inspection, every decision, every reason, stored against the job. When a customer raises a warranty claim six months later, you can prove the part left your facility right.
Fixed fee, phased delivery.
£3,200-£10,000 for build, ~£150-£400/month for hosting + accuracy monitoring
From £3,200excluding VAT
QC inspection
- Workflow audit + scope
- Build, integrations, and tuning to your real data
- Deployment, handover and agreed access controls
- Hosting, AI usage and ongoing support quoted separately
What people ask us.
01Is this actually accurate enough to trust?
Yes, provided you set the confidence thresholds sensibly and keep humans in the loop on edge cases. We typically run with the AI handling 80-90% of inspections fully autonomously, with the rest reviewed by a human. The compound effect is that humans only look at hard cases, where they're much more reliable.
02What about ISO 9001 and traceability?
Every decision is logged with the input image, the schema applied, the confidence scores, and the outcome. That's a cleaner audit trail than a paper QC log signed by a person who looked at 200 parts that day.
03Does this replace our QC inspector?
It changes their job, not eliminates it. They become the person who reviews flagged cases, tunes the system, and handles complex inspections, much less boring, much more skilled. Most clients keep the same headcount and just take on more work.
04What about parts that need physical measurement?
AI vision can't replace a vernier gauge. But it can flag "this looks visually wrong, take a measurement", which is often the trigger that's missing today.
05Where does the data go?
Photos and decisions stay in your environment. Models we use don't train on your data. We can run fully on-premise if that's a requirement.
Which industries this suits.
Other AI work we build.
Keep exploring
Build this for your business.
What could work
better for you?
A new website. More customers. Less admin.
Tell us where you want to get to. Chris or Kay will reply within one working day.