Ritual is pioneering a new approach to on-chain artificial intelligence by leveraging classical machine learning (ML) techniques, offering a cost-effective and efficient alternative to large language models (LLMs). By utilizing regression and tree-based models, Ritual aims to enhance smart contract intelligence without the overhead of heavy models. The company's solution, EVM++ with ONNX sidecars, enables classical ML inference directly on-chain. This setup allows developers to access pre-trained models from platforms like Hugging Face and Arweave, and execute them through a dedicated ML sidecar. This approach ensures efficient and scalable inference, optimized for performance without the burden of LLMs. Ritual's innovation demonstrates that on-chain intelligence can be achieved with smaller, classical ML models, making AI more practical and accessible for web3 applications. This method not only enhances interoperability across AI frameworks but also provides customizable preprocessing, ensuring seamless integration into blockchain environments.