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PrivyAI
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About PrivyAI
PrivyAI enables fully private AI interactions by running large language models entirely on local devices, eliminating cloud telemetry and external data exposure. It supports leading open models such as Llama 3, Gemma 2, Qwen 2.5, Mistral 7B, Phi-3, and Bonsai 27B, all optimized for low memory usage and fast first-token latency through quantization. The tool provides a local API proxy that is fully compatible with the OpenAI API, allowing seamless integration with existing scripts, IDEs, and enterprise applications via Wi-Fi or USB hotspot without requiring cloud connectivity. PrivyAI includes RAM diagnostics to assess hardware stability before model download and supports air-gapped deployments for industries with strict regulatory requirements, such as healthcare and legal services. It is designed to comply with stringent standards like HIPAA and GDPR by ensuring zero outbound network activity and no data retention during inference. Developers can leverage the tool for offline, high-performance AI workflows while maintaining full control over data privacy and infrastructure. The platform is particularly suited for organizations prioritizing data sovereignty, security, and compliance in AI-driven operations.
Key features
- On-device neural execution of GGUF quantized models
- Local API proxy with OpenAI v1 schema compatibility
- Unified RAM diagnostics before model download
- Enterprise air-gapped deployment support
- HIPAA and GDPR compliance architecture
- Wi-Fi and USB hotspot connectivity for local tools
- Mathematically proven hardware data isolation guarantee
- Model catalog with free and Pro Pass options
Use cases
- Secure clinical data analysis for HIPAA-compliant environments
- Offline legal document review with zero data retention
- Local development tool integration via API proxy
Pros
- Runs AI models entirely on-device with zero cloud telemetry
- Supports multiple open LLMs including Llama 3, Gemma 2, and Qwen 2.5
- Provides a local API proxy compatible with OpenAI’s v1 schema
- Includes RAM diagnostics to prevent hardware instability
- Offers enterprise-grade air-gapped deployment options
Cons
- Requires compatible hardware with sufficient RAM for selected models
- Limited to mobile devices supporting Apple Metal or Snapdragon NPU
- No cloud-based fallback if local execution fails
Frequently asked questions about PrivyAI
What is PrivyAI and how does it ensure 100% privacy?
PrivyAI is a platform that runs large language models locally on supported devices without cloud telemetry, ensuring all AI interactions remain private and isolated. It executes models natively on hardware using zero outbound network sockets, preventing any data retention or exposure during inference.
Who should use PrivyAI?
PrivyAI is designed for developers, medical teams, legal counsel, and regulated industries such as healthcare and legal services that require strict compliance with standards like HIPAA and GDPR. It is also suitable for users needing local AI capabilities without cloud dependency.
How does the local API proxy work in PrivyAI?
The local API proxy is OpenAI API-compatible and allows users to connect scripts, IDEs, and enterprise tools directly to their device via Wi-Fi or USB hotspot. This setup eliminates cloud latency and token subscription fees while maintaining zero cloud telemetry.
Does PrivyAI support enterprise-grade deployments?
Yes, PrivyAI supports enterprise-grade air-gapped deployments, custom model weights, and enterprise MDM sandboxes for regulated industries. It ensures zero compromise on customer privacy or proprietary intellectual property.
What models are supported by PrivyAI?
PrivyAI supports flagship open models such as Llama 3, Gemma 2, Qwen 2.5, Mistral 7B, Phi-3, and Bonsai 27B, all quantized for low memory consumption and optimized for instant first-token latency.
How can I get started with PrivyAI?
Users can download the PrivyAI mobile app, which includes a unified RAM diagnostics feature to ensure hardware stability before model download. The app provides access to the model catalog and allows local execution of supported models.
