SOFTWARE · THE SPINE

Vale Platform

The processing core of the Vale system. Bring imagery from any source, ours or yours, and let AI distill your data into actionable insights. Built for scale.

Source-agnostic by design

If it produces imagery, the platform can analyze it.

Vale Optical Payload
Mesh-grid cameras
Drone & aerial imagery
Aerial imagery
Trail cameras
INGEST

Any format, any source. Batch or stream.

ValeRESOLVE

AI + Depth detect, classify, and count.

DELIVER

Density maps, trends, and exports.

Capabilities

From raw imagery to wildlife intelligence.

Detect and classify at scale

Process thousands of trail-camera images and full aerial survey datasets in one pass. Distributed GPU and CPU workers handle the volume, so you get results instead of a backlog.

Train models on your own data

Fine-tune detection and classification on your labeled imagery, improving accuracy for your species, your terrain, and your camera setups.

Full taxonomy with geofencing

Every detection carries complete taxonomic information, and region-specific constraints filter out species that do not belong in your area.

Distance and size from one image

Depth estimation reads range and animal size from ordinary RGB photos, with LiDAR and RGB fusion when you need precise 3D localization.

Aerial surveys, no manual review

Large GeoTIFFs and aerial frames run through overlapping tile detection automatically. Cover wide regions and count what is there without page-by-page review.

Reports you can defend

Standardized CSV and PDF reports with detections, camera locations, study areas, and summary statistics, ready for stakeholders.

Ingest from anywhere

Pull from connected trail cameras, RTSP streams, S3 buckets, and direct uploads, organized by camera station and location on map views.

Inside the pipeline

How the platform reads one frame.

One trail-camera image, run end to end through the Animalis models. Detection finds the animal, classification places it in the full taxonomy, landmark detection maps its posture, and depth reads range and size, no second sensor required.

Raw trail-camera frame of an elk
01 · RAW A single RGB trail-camera frame.
Animal detected and classified to species
02 · DETECT + CLASSIFY The animal is localized and placed in the taxonomy, here Cervus elaphus, at full confidence.
Landmarks mapped on the animal
03 · LANDMARKS We detect key landmarks across the body to determine aspects like movement direction, biomorphic measurements, and unique traits.
Depth map of the scene
04 · DEPTH Depth reads range and size from the same RGB frame.

In the field

The platform in your pocket.

The Vale mobile app carries the same intelligence into the field, offline-first, with a live 3D map of every camera, detection, and trail on your property.

  • 3D PROPERTY MAP A tactical satellite-and-terrain view with every camera and its field-of-view cone.
  • LIVE TELEMETRY Battery, signal, and last-seen for every node, updated as they report in.
  • INDIVIDUALS & INVENTORY Track named animals and build a season-long property inventory for large-property hunt management.
  • SHARED WITH YOUR CREW Share maps, cameras, and inventory with everyone you hunt with.
  • WAYPOINTS & TOOLS Drop stands, blinds, and feeders, measure distance and area, draw trails and fence lines.
  • OFFLINE-FIRST Everything works without signal and syncs the moment you are back in range.
Vale mobile app: 3D property map with camera field-of-view cones

At a glance

Platform details

DeploymentCloud or on-premise
InputsRGB, thermal, LiDAR point clouds
ModelsDetection, classification, landmarks, depth, segmentation
TaxonomyFull multi-level taxonomy with geofencing
OutputsDensity maps, PDF reports, CSV / GeoJSON
IntegrationAPI, bulk import, third-party sources
Runs anywhereGPU or CPU workers, batch or stream
LicensingPer-seat or organization-wide

ROI calculator

What automated review saves you.

1,000,000
$36

A trained technician reviews roughly 180 images an hour for species ID and counting; Vale processes about 0.2 seconds an image on a single GPU, around 18,000 an hour. Producing population-density estimates by hand can take about 15x longer per detection, which Vale also automates. Loaded labor rate based on US biological-technician wages.

Sources: iWildCam 2018; Norouzzadeh et al. 2018 (PNAS); Howe & Buckland 2017; Haucke et al. 2022. Methodology and references →

5,000Review hours saved / year
$180,000Labor cost saved / year
~15x lessHands-on density work

Already have imagery? Start processing it.