LazAI has officially launched its testnet, providing developers with an environment to build, test, and deploy decentralized AI agents. The platform introduces a framework for developing AI systems that incorporate tokenization and privacy-preserving technologies within a Web3 ecosystem. The LazAI testnet offers access to the Alith Framework, featuring cross-language SDKs in Python, Node.js, and Rust. Developers can utilize high-performance inference capabilities, streamlined APIs for data queries, and real-time monitoring tools. The testnet supports contributions of real data, development of AI agents, and the use of on-chain privacy-preserving proofs. Its architecture emphasizes composability, interoperability, horizontal scalability, and customizable workflows to support future upgrades. Key Features of the LazAI Platform: Alith Framework: A development toolkit designed to facilitate AI inference across multiple model architectures. The framework offers native blockchain integration, allowing for direct data submission and model deployment within a decentralized infrastructure. Data Anchoring Token (DAT): A token-based mechanism supporting AI asset management through cryptographic verification and proof-of-contribution validation. The DAT enables transparent revenue-sharing processes via on-chain data anchoring and evaluation workflows on the testnet. Scalable Architecture: The platform includes components such as the DAT Marketplace for AI-native assets, LazPad for AI agent deployment, and DeFAI protocols for building AI-driven applications. The infrastructure supports modular computing with verified execution, decentralized data feeds, model hosting, and oracle integration.