Ground truth, at industrial scale.
Models are only as honest as their labels — so we run our own labeling floor.
First we teach it. Then it sees.
Two halves of the same discipline, side by side. On the left, our annotators draw the vector spaces that teach a CNN what test objects are. On the right, the trained models at work — including a separate model that reads what the color-coded litmus strips mean, through ordinary web cameras.
Labeling, built into the product.
The same discipline the floor runs, shipped as software — PROOF's guided labeling workflow: gather the raw webcam footage, label it against the taxonomy, validate every batch. Bounding boxes drawn on live test sessions, by design.
Roboflow-class tooling.
Bounding boxes, segmentation, classification — pipelines that move imagery from S3 to training-ready, with every label QA'd.
A managed bench, not gig work.
Our Lagos labeling team works inside your taxonomy with trained reviewers — consistency a crowd marketplace can't promise.
Labels, versioned like code.
Release-numbered datasets, relabeling passes, synthetic augmentation — so every model can name the exact data it learned from.
Ready when you are.
Start something. Fix something. Scale something.
Whichever door fits, an engineer reads your note — we'd love to work with you.
Start with Punch.
A new build — raw data to production software, with an honest go/no-go on the way.
Start the conversation 02 · SWITCH
Switch to Punch.
A demo that never shipped? We take over half-built AI — audit it, finish it, or call it honestly.
Get a second opinion 03 · SCALE
Scale with Punch.
An embedded senior team shipping inside your org, month over month — knowledge that stays.
Meet your teamTalk to an engineer.
Pick whichever is easiest — every option reaches a real engineer, never a sales queue.