A single captured shelf, refined into structured truth — by twelve models that learn from one another, and get sharper with every single click.
Like a refinery turns crude into fuel, Kanops refines a raw shelf photograph into structured, decision-ready intelligence — in five stages.
Idaten-K detects shippers & displays; Themis identifies thousands of shelf-edge labels.
→Gary maps products to labels, reconstructing the physical realogram.
→Two engines extract brand, price and label text at 93.1% yield.
→Matched against 138,235 products and 5,821 brands for SKU-level resolution.
→Area-weighted Share-of-Shelf, price positioning and compliance — via Delphi.
These five stages draw on 15+ models built, 6+ live — Idaten-K, Themis, Zygos, Kanon, Moneta, Mercator, Vertumnus, Chronos, OCR and more — each retrained and refined daily.
Every model is wired to the others. A single human fix cascades through Mercator, Vertumnus, Themis, Chronos, OCR and Idaten-K — 1.8M+ cross-learning entries and counting, improving performance without retraining.
A correction in one model provides context that improves the others — detection, pricing and classification move together.
Models are retrained and refined daily — the platform is measurably sharper this week than last.
Request access and we'll run a live read-out against a category you want to grow — showing where to sharpen execution, win share and generate demand.
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