The current model of LLM (Large Language Models) tool use, known as “function calling,” confines developers and users, prioritizing platform benefits over privacy and control. Users’ data is sent to third-party servers, creating privacy issues, while a rigid API structure locks users into specific providers. Additionally, the execution environment lacks transparency, making it unsuitable for sensitive tasks, and incurred costs continue to rise with each tool call. Orakle aims to shift this paradigm by granting users autonomy over tool execution. With a two-phase skill matching system, it ensures high accuracy and efficiency, executing processes locally within a secure environment. This framework leads to improved privacy, competitive performance, and no ongoing usage fees after initial hardware costs. By returning control to developers and end-users, Orakle champions a decentralized approach in AI development, marking the transition to user-owned applications and a departure from centralized AI systems.
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Unlocking the Future: Why AI Applications Should Be Yours—The Orakle Manifesto by Rubén Gómez | June 2025
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