Showing 4 open source projects for "personal cloud"

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  • 1
    OpenJarvis

    OpenJarvis

    Personal AI, On Personal Devices

    OpenJarvis is an open-source framework designed to build personal AI agents that run primarily on local devices rather than relying on cloud infrastructure. Developed as part of the Intelligence Per Watt research initiative, it focuses on improving the efficiency and practicality of on-device AI systems. The framework provides shared primitives for building local-first agents, along with evaluation tools that measure performance using metrics such as energy consumption, latency, cost, and accuracy. ...
    Downloads: 186 This Week
    Last Update:
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  • 2
    CoPaw

    CoPaw

    Your Personal AI Assistant; easy to install, deploy on local or coud

    CoPaw is a personal AI assistant designed to run on your own machine or in the cloud, giving you full control over memory, models, and data. Built by the AgentScope team, it connects to multiple chat platforms—including DingTalk, Feishu, QQ, Discord, iMessage, and more—through a single unified assistant. CoPaw supports both cloud-based LLM providers and fully local models such as llama.cpp, MLX, and Ollama, allowing you to operate without API keys if preferred. ...
    Downloads: 8 This Week
    Last Update:
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  • 3
    Flowly AI

    Flowly AI

    Flowly is 100x faster than OpenClaw

    ...Flowly also includes voice capabilities, enabling real-time phone interactions using speech-to-text and text-to-speech systems. Overall, it provides a powerful, extensible, and privacy-focused alternative to cloud-based AI assistants.
    Downloads: 5 This Week
    Last Update:
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  • 4
    SafeClaw

    SafeClaw

    Chat with it via text and voice

    SafeClaw is an open-source, entirely local alternative to cloud-based AI assistants like OpenClaw, enabling users to build a personal assistant that runs on their own machine without incurring API usage charges or exposing data to third-party services. It emphasizes privacy and predictability by using traditional programming, rule-based intent parsing, and established machine learning tools rather than large language models, meaning there are no per-token API costs and deterministic behavior. ...
    Downloads: 1 This Week
    Last Update:
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