Privacy AI Offline AI Chatbot

No Internet? No Problem! Privacy AI Works Anywhere, Anytime!

Privacy AI is a revolutionary local AI chatbot for iOS that ensures your data remains safe and private by working entirely offline. Your information never leaves your device, making it a secure solution for all your AI needs. With a one-time purchase or by subscription, you can access Privacy AI across all your Apple devices. Designed for everyone, Privacy AI offers easy-to-use features for generating text, assisting with language tasks, and much more. Utilizing the latest AI models and state-of-the-art quantization techniques, Privacy AI delivers a high-quality on-device AI experience without compromising your privacy. Get creative and productive, anytime and anywhere, with Privacy AI.

Customizable AI Experience

Privacy AI offers advanced customization options, allowing users to set the sampling temperature, system prompt, and Top-p value according to their preferences. This feature provides greater control over the AIs behavior and output, ensuring a more personalized and tailored AI interaction.


Harness the Power of Open-Source AI with Privacy AI

Privacy AI opens the door to the vast possibilities of AI with support for an extensive selection of open-source LLM models, including Llama 3, Google Gemma, Microsoft Phi-3, Mistral family, and many more. This wide range of model support ensures that users on iOS, iPadOS, and macOS can fully utilize the power of AI, customized specifically for their devices.

Universal Access with one time purchase or with Subscriptions

Ditch the subscriptions for a smarter choice with Privacy AI. A single purchase unlocks the app across all Apple platforms—iPhone, iPad, and Mac—while enabling Family Sharing for up to six relatives. This approach not only simplifies access but also amplifies the value of your investment, making digital privacy and intelligence universally available in your family.

Superior Model Performance With State-Of-The-Art Quantization

The core of Privacy AIs superior model performance lies in its use of the state-of-the-art quantization algorithms. While quantizing LLMs for on-device inference, outlier values in LLM weights tend to have a marked adverse effect on text generation quality. Our quantization handles outliers by employing an optimization-based learnable weight clipping mechanism, which preserves the models weight distribution with exceptional precision. RTN (Round to Nearest) quantization, used by popular open-source LLM inference frameworks and apps based on them, does not handle outlier values during quantization, leading to inferior text generation quality. Quantization, paired with optimized model-specific Metal kernels, enables Privacy AI to deliver text generation that is not only fast but also of the highest quality, significantly raising the bar for on-device LLMs.


End User License Agreement:
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