Private Mind
Local, private AI that fits in your pocket
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Maciej Rys

Private Mind - Local, private AI that fits in your pocket

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Private Mind represents a new era of AI—powerful, personal, and completely offline. Built around the belief that AI should live entirely on your device, Private Mind opens the door to a new kind of experience: fast, secure, and fully private.

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Jakub Chmura
Maker
📌

Hey Product Hunters ✌️

We're excited to launch Private Mind - a free, open-source app that demonstrates the incredible potential of local AI inference running entirely on your device.

Why local AI matters?

  • Your conversations stay completely private

  • You get lightning-fast responses with no internet dependency

  • You maintain full control over your data

Private Mind showcases what's possible when powerful LLMs run directly on your hardware 🚀.

Download the app on App Store or Google Play.

If you're curious about the implementation details, we highly encourage you to check out our GitHub repository.

We believe on-device AI represents the future of truly private, accessible intelligence - and we'd love your feedback on what we've created 🫶🏻

Maciej Rys
Hunter

The real game-changer would be adding local RAG capabilities to Private Mind - imagine being able to upload your PDFs, documents, and personal files to enhance the LLM's knowledge base, all while keeping everything completely private and on-device.

Think about it: your personal research papers, company docs, project notes - all accessible to your AI assistant without ever touching the cloud. True knowledge augmentation that respects your privacy.

And yes... this might just be what we're working on next 👀

Joey Judd

No way—an AI that runs locally and keeps everything private? That’s exactly what I need for travel days when I don’t trust public WiFi. How do updates work?

Mateusz Kopciński
Maker

@joey_zhu_seopage_ai Exactly, nothing sent to cloud, everything off-line, perfect for when you are on an airplane with access to power outlet! What updates do you have in mind?

Cruise Chen

Love the idea of an entirely on-device AI. How does Private Mind handle incremental updates? I’m imagining I’m on a flight with no Wi-Fi and suddenly need to summarise a 50-page PDF—will the model still be snappy on a two-year-old MacBook Air, or should I expect noticeable lag?

Norbert Klockiewicz
Maker

@cruise_chen Hi, local llms by design have a short context window so feeding model with 50 page PDF isn't really possible. However in the next version we will introduce RAG, a feature which will allow you to upload PDFs and documents of any length that will be stored in offline knowledge base, therefore when you ask the llm about something from the document it will retrieve only the most important information and thanks to that the context window won't be bloated and the model won't slow down.

Jeremy Yan

so it's running LLM models on mobile? which models do you support? @norbert_klockiewicz

Norbert Klockiewicz
Maker

@mout Hi, we support plenty of models including LLaMA 3.2, qwen2.5, qwen3, smollm2 and a few more, you can find all the models on models page in application and on our organization on huggingface. If you don't know which to choose I would suggest using LLaMA 3.2 1B spinquant as it offers great performance without overheating your phone :D

lavendren pillay
Good day I downloaded the app from the Play Store I clicked to access it nothing happening can you assist
Jakub Chmura
Maker

Hi@lavendren_pillay

thank you for reaching out and for downloading the app! I’m sorry you’re having trouble accessing it. Could you let me know which device and Android version you’re using? Also, when you try to open the app, does it crash, or does the screen just stay blank?