Adaptive AI from Observation to Action Adaptive AI from Observation to Action Adaptive AI from Observation to Action

SightTrack provides high-quality training data to build breakthrough AI models for wildlife conservation. Join thousands of citizen scientists creating the world's largest biodiversity dataset.

The Problem

Wildlife monitoring at scale is broken

Despite the rise of citizen science platforms, global biodiversity data is still plagued by three major problems:

Most observations are dispersed and fragmented. Remote areas, rare species, and seasonal changes are underreported, creating data islands that are scientifically unreliable.

Without standardized methods, many photos and records are incomplete or inaccurate. This makes it difficult for researchers to use citizen science data in serious ecological models.

People want to help, but don't know how. Conservation advice is often vague and disconnected from everyday life. As a result, interest doesn't lead to impact.

Problem Visualization

Our Solution

From everyday observations to ecological impact

SightTrack bridges the gap between public enthusiasm and scientific conservation through an AI-powered platform that turns local wildlife sightings into meaningful action

Our app guides users to biodiversity blind spots using intelligent sampling recommendations, and teaches simple scientific methods (transects and quadrats) to collect structured, accurate data

Once data is collected, our Action-Track engine translates it into precise ecological actions

A complete loop empowers individuals and fuels real conservation, all while enriching scientific biodiversity models

Solution Visualization

Powering conservation at scale

70K+ Identifiable Species
95% Vision Accuracy
150+ Countries Covered

Global Impact

Data that drives decisions

SightTrack isn't just another nature app. It's a high-impact data engine designed to support global biodiversity recovery at every level

By guiding users to underreported areas and species, SightTrack contributes high-quality, structured biodiversity data to global databases like GBIF and iNaturalist. This improves the accuracy of species distribution models, ecosystem risk assessments, and conservation planning worldwide.

For Researchers

Access structured, high-quality biodiversity data with precise geospatial and temporal metadata for your conservation models.

For the Public

Turn your nature walks into meaningful conservation action with AI-guided observations and personalized impact tracking.