Products that see what humans miss.
For manufacturing, healthcare, retail, and logistics teams. We build camera-and-image AI that works in the real world — not just the demo — and keeps getting more accurate as conditions change, with the record-keeping regulated industries need.
An AI that spots defects in the demo and one that spots them on a real factory floor are two different things.
It's easy to score 95% on a tidy test set. It's hard to stay accurate when the real world shifts — the lighting changes, a new product variant appears, a supplier changes the packaging. We build the feedback systems that keep the AI accurate over time, not just at launch.
We use the best available vision AI for each job — and we build everything around it too: the tools for labeling your images, version control for the AI, and the setup to run it wherever you need. A model is only as good as the system around it.
For regulated industries — healthcare, financial ID checks, food safety — we build the paper trail alongside the AI: a record of every decision it makes, an explanation of why, and the ability to roll back to any earlier version for an audit.
What we build.
Spotting defects on the line
Catches scratches, misalignments, missing parts, and packaging faults in real time — fast enough for your production line, and without crying wolf so often that your team tunes it out.
ID & document checks
Reads passports, ID cards, and driving licenses, confirms the person is really there, and flags fraud — with the audit records financial regulators expect.
Medical image analysis
Finds and outlines what matters in X-rays, CT and MRI scans, tissue slides, and skin images — with the documentation support needed for medical-device approval (FDA/CE).
Shelf & store monitoring
Uses your existing security cameras to track stock levels, check shelves are laid out as planned, and understand how customers move through the store.
Logistics & warehouse automation
Spots packages, reads barcodes and labels, inspects pallets, and automates loading docks — connected to your warehouse systems.
AI that keeps getting smarter
The system saves the images it found hardest, a human labels them, and the AI learns from them — so accuracy climbs over time instead of quietly slipping.
How we build it.
Review your images
We look at the photos and video you already have: quality, variety, and the tricky cases. Then we plan how to capture whatever's missing before the AI meets the real world.
Pick the right AI
We choose the AI based on how fast it must be, how accurate, and what hardware it will run on. We set the targets in writing before training starts.
Train & test
We train the AI on your real-world images, test it against the hard cases — not just the easy ones — and keep improving until it hits the agreed targets.
Install it
We run the AI wherever it makes sense — on small devices right next to the camera, or in the cloud — tuned to run fast on whatever hardware you have.
Keep it sharp
We set up the feedback loop: hard cases get flagged, a human labels them, the AI retrains, and every version is tracked. Accuracy compounds — it doesn't drift.
Tools we use.
Frequently asked.
5 questions answered. Still have one? Reach out.
For a narrow task, 500–2,000 labeled examples can be enough for a production-ready system. For complicated jobs with many categories, you typically need 5,000–20,000+. We help you figure out the right number — and we have tools that speed up the labeling.