EU-hosted wildlife AI, with a human in the loop

When footage arrives, our wildlife AI detects animals and suggests a species, with a confidence score. The detection runs on European infrastructure — not a black-box overseas cloud API — which matters when your data describes protected species and sensitive locations.

Confidence, not certainty

No model is right every time, especially on a dark, motion-blurred night frame. So a low-confidence detection does not get quietly filed as fact — it goes to a review queue, where a person confirms or corrects it. Those corrections are kept with the detection, so your record reflects what was actually there, and the model's blind spots become visible instead of hidden.

Built for the region you work in

Look-alike species are a common source of error — a lynx read as a bobcat, a red deer confused with a North-American relative. By hinting the model with the region a camera sits in, we rule out species that simply do not occur there, which noticeably improves the labels you start from.

Why it matters

For research and conservation, credibility is everything. Transparent AI, a human check where it counts, and data that stays yours and in Europe — that is the combination we think a monitoring platform should stand on.