ChainStream is a cross-platform mobile and desktop inference framework that streams partial outputs from large language models in real time. It breaks LLM inference into submodel chains, enabling incremental token delivery and reducing perceived latency. Developers can integrate ChainStream into their apps using a simple C++ API, select preferred backends like ONNX Runtime or TFLite, and customize pipeline stages. It runs on Android, iOS, Windows, Linux, and macOS, allowing for truly on-device AI-driven chat, translation, and assistant features without server dependencies.

Clariti is a privacy-first AI assistant designed for confidential tasks. Unlike traditional AI, Clariti operates 100% offline with zero cloud storage, ensuring maximum data privacy. Whether managing health data, analyzing documents, optimizing schedules, or transcribing voice notes, Clariti integrates seamlessly with your device’s data. It's built on Apple’s Neural Engine for lightning-fast performance, making it a reliable assistant for professionals, health-conscious individuals, busy executives, and privacy enthusiasts. Simply put, Clariti transforms your device into a powerful, private AI companion that respects your data and boosts productivity without the need for an internet connection after the initial setup.

Venice is a platform designed to provide powerful, censorship-resistant AI models while ensuring user privacy. Unlike traditional AI providers, Venice operates through a decentralized network, ensuring that all data remains on the user's device and is not stored on company servers. The platform supports various advanced AI models for text, image, and code generation, making it a versatile tool for developers and agents wanting to build unrestricted, high-performance AI applications.

Phala Network is designed to provide a privacy-first cloud computing environment, allowing developers to run applications in line with privacy requirements. Leveraging a decentralized network of nodes, Phala ensures sensitive data remains confidential while still allowing for compute power to develop machine learning models and other computational tasks. Users benefit from a secure execution environment that not only protects their data but also incorporates seamless integration with existing blockchain applications.