Models are only as honest as their labels — so we run our own labeling floor.
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.
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.
Bounding boxes, segmentation, classification — pipelines that move imagery from S3 to training-ready, with every label QA'd.
Our Lagos labeling team works inside your taxonomy with trained reviewers — consistency a crowd marketplace can't promise.
Release-numbered datasets, relabeling passes, synthetic augmentation — so every model can name the exact data it learned from.
Start something. Fix something. Scale something.
Whichever door fits, an engineer reads your note — we'd love to work with you.
A new build — raw data to production software, with an honest go/no-go on the way.
Start the conversation 02 · SWITCHA demo that never shipped? We take over half-built AI — audit it, finish it, or call it honestly.
Get a second opinion 03 · SCALEAn embedded senior team shipping inside your org, month over month — knowledge that stays.
Meet your teamPunch AI scopes it with you live — in voice or text — then hands off to the engineer who’d actually build it. Start talking now.


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