Vale provides an AI‑driven platform that automatically detects, classifies, and measures wildlife in trail‑camera images, converting flat photos into three‑dimensional, geolocated insights. By estimating real‑world distances and anchoring detections to terrain data, the system delivers searchable maps and dashboards that show species distribution, activity timelines, and movement patterns, enabling researchers and land managers to turn raw image streams into actionable wildlife intelligence.
Funding
Funding not disclosed
Founders
Product
Problem
Ecologists and land managers must manually review large volumes of trail‑camera images to identify species, estimate animal locations, and understand movement patterns, which is labor‑intensive and often lacks precise spatial context.
Solution
Vale offers an AI‑driven platform that automatically detects, classifies, and measures wildlife in trail‑camera photos. The system estimates real‑world distances for each detection, converting flat images into three‑dimensional insights anchored to the camera’s geographic location. By mapping detections and movement vectors onto terrain data, users can quickly visualize where and when animals are present, turning raw image streams into actionable wildlife intelligence that aligns field time with specific places.
Target Audience
Primary customers are wildlife researchers, conservation NGOs, and land‑management agencies that rely on trail‑camera data to monitor animal populations and habitat use.
Features
- Automated species detection and classification for every image in a camera trap dataset
- Calibrated AI models that estimate real‑world distance, providing 3D positioning from 2D photos
- Geolocation anchoring of each detection, integrating movement vectors with terrain maps
- Continuous processing pipeline that transforms raw images into searchable, mapped wildlife data
- Dashboard visualizations that display species distribution, activity timelines, and spatial patterns