Point a camera at the problem — and get a number.
Computer vision that turns a camera into a sensor — inspecting a line, counting from a photo, capturing an ID, watching for safety — with a human check wherever a missed read is expensive.
A camera already sees everything on your floor. Vision makes it count.
Most sites are already filmed — the line, the gate, the yard, the shelf. That footage is a sensor nobody is reading. Computer vision turns it into data: a defect caught before it ships, a count taken without a clipboard, a hazard flagged the moment it appears.
We build vision tuned on your own images, not a generic model that has never seen your product. And we are clear-eyed about the cost of a miss: wherever a wrong or missed read is expensive, a human confirms the edge case. Vision does the volume; a person holds the line where it matters.
- Models tuned on your own images, product and conditions
- Quality inspection, counting, capture and monitoring from ordinary cameras
- A human check wherever a missed read is costly
- Wires into the ERP, IoT and dashboards we build alongside it
Sight turned into a decision.
From a defect on the line to a count on a shelf, we make the camera produce a number your systems can act on.
Quality inspection on the line
Vision checks each item as it passes — for defects, missing parts, wrong labels — faster and more consistently than a tired eye at the end of a shift. Borderline cases route to a person, so the line catches what matters without over-rejecting good stock.
Count & condition from a photo
Count units on a pallet, stock on a shelf or vehicles in a yard from a single photo, and grade their condition while you are at it. What used to be a manual tally with a clipboard becomes a number your systems can act on.
ID & document capture
Capture an ID card, a licence or a form through a camera — reading the fields and checking the image is genuine and legible — for onboarding, verification and check-in. It pairs with our document AI so capture and extraction are one flow, not two.
Footfall & zone analytics
Count people, measure dwell and see how a space is used — a store, a stall, a queue — without tracking anyone personally. It tells you where attention goes and where it stalls, turning a camera feed into a plan you can act on.
Safety & compliance monitoring
Flag the things that should not happen — a missing helmet, a person in a restricted zone, a blocked exit — the moment they appear, so a supervisor is alerted in time to act. The point is prevention, not a report written after the incident.
Tuned models & a human check
Generic models fail on your specific product and lighting, so we tune on your own images and keep improving from real corrections. And wherever a missed read is costly, a person confirms the edge case — vision handles the volume, judgement stays where the stakes are.
The camera does the volume; a person holds the line.
Vision tuned on your images, with a human check exactly where a miss is expensive.
A feed becomes a signal.
Cameras you already have start producing counts, grades and alerts your team can act on in time.
Tuned on your floor, not a benchmark.
We train on your own images and conditions, and decide up front where a person must stay in the loop.
The read
Pin down exactly what the camera must decide — a defect, a count, a hazard — and what a miss costs.
The images
Gather real footage from your own cameras and conditions, the good frames and the awkward ones.
The model
Train and tune vision on your images until it holds up on your product, not a benchmark's.
Human in the loop
Set confidence thresholds so costly edge cases route to a person instead of passing unseen.
Wire & watch
Connect it to your dashboards, ERP or IoT, then monitor accuracy and retune as conditions change.
Vision is a sensor for the rest of the stack.
A read is only useful where it lands — feeding the document flow, or an assistant your team can ask.
Things you might be wondering.
Do we need special cameras?
Will it work on our specific product?
What about the reads it gets wrong?
Does this connect to the rest of our systems?
A count or a check someone still does by eye?
Tell us what the camera should catch. We will tell you honestly what vision can read reliably — and where a human still should.