AI-powered systems for wildlife monitoring and conservation intelligence.
AI ZIPs define protocols for machine learning models that monitor wildlife populations, detect poaching activities, analyze habitat health, and power intelligent conservation agents. Our zLLM (training-free) approach enables efficient, decentralized AI deployment.
Multi-agent SDK for building conservation AI agents for habitat monitoring, poaching detection, and migration tracking
On-chain attestation protocol for verifying AI model integrity, provenance, and training data lineage
Token incentive mechanism for contributing compute resources to distributed AI model training on the Zoo network
Mandatory ethics review process for AI models deployed on the Zoo network ensuring safety, fairness, and conservation alignment
Standard for combined vision and audio AI models for automated wildlife species identification and monitoring
Conservation-aware fungible token standard for the Zoo ecosystem with impact tracking and auto-donation extensions
Conservation NFT standard with species metadata, provenance chain, and royalties directed to conservation funds
Multi-token standard for batch operations supporting conservation badges, in-game items, and multi-asset portfolios
ERC-6551 token-bound accounts enabling wildlife NFTs to own assets, receive donations, and accumulate conservation history