About Rastrum
Rastrum is an open-source biodiversity observation platform that combines computer vision, audio analysis, and expert curation to identify species from photos, videos, audio, and indirect evidence.
Making biodiversity knowledge accessible to everyone — from field researchers to curious hikers — so every observation can drive conservation.
Our Vision
The Problem
Species identification tools are fragmented across platforms, locked behind language barriers, and rarely work offline. Most existing models are trained on data from North America and Europe, leaving megadiverse regions like Latin America critically underserved.
The Solution
Rastrum unifies photo, audio, and video identification into a single open platform powered by multiple AI models and validated by community experts. Every observation feeds a growing dataset that strengthens regional accuracy and fuels real conservation action.
How It Works
Observe
Capture photos, audio, or video of any species in the field.
Identify
Our AI pipeline analyzes your evidence using PlantNet, BirdNET, and Claude Vision.
Contribute
Validated observations join a growing open dataset for conservation and science.
Roadmap
Foundation
- Astro skeleton + Supabase schema
- Photo ID MVP with PlantNet
Intelligence
- Claude Vision integration
- Observation log + GPS tagging
Community
- Audio ID with BirdNET
- Expert validation system
Full Platform
- Video analysis support
- Offline mode + Darwin Core export
Next Frontier
- Regional ML models from community data
- AR species overlay
Conservation Impact
Built With
Astro
Fast, modern web framework for static-first delivery
Supabase
Open-source backend for database, auth, and storage
PlantNet
Specialized AI for plant and fungi identification
BirdNET
Neural network for bird and wildlife audio recognition
Claude Vision
Advanced multimodal AI for general species identification
Open Source
Rastrum is AGPL-3.0-licensed and community-driven. Every observation, every validation, every line of code strengthens the global biodiversity knowledge commons.
GitHub