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PrivateGPT

PrivateGPT lets you ask questions about your documents using AI, all without an internet connection. Your data stays 100% private and secure on your own computer or network. It's a powerful, open-source tool for building smart applications that understand your private information without ever sending it away.

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About PrivateGPT

Who It's For

PrivateGPT is for developers and businesses needing AI that keeps data private. It's perfect if you want to use advanced AI models with your own sensitive documents without sending anything outside your network. You keep full control of your information.

What You Get

You get an open-source system to build AI assistants. These assistants can "talk" with your documents (like PDFs, CSVs) even when offline. It includes tools for handling documents, processing data, and an API that works like OpenAI's, but fully local.

How It Works

The tool runs entirely on your local computer or network. It reads your documents, finds important details, and uses AI to generate answers. This means your private data never leaves your environment. You can set it up on your servers and customize it for different departments.

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Give your AI a memory

Build one knowledge base all your AI tools draw from, kept current with your review.

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Features & Capabilities

🔒 Data Privacy & Local Control

Fully Local & Offline Execution

Run Large Language Models (LLMs) and AI applications entirely within your private environment, without an internet connection.

100% Private & Secure

Ensures your sensitive data never leaves your local environment, maintaining complete privacy and security.

Private Knowledge Base Integration

Allows tapping into your confidential documents and data sources to power AI interactions privately.

🧠 AI & Document Interaction

Context-Aware Document Q&A

Build AI applications that can answer questions and derive insights directly from your specific documents.

Broad Document Type Support

Interact with a wide range of document formats including CSV, PDF, TXT, HTML, DOCX, PPTX, and Markdown files.

Local LLM Integration

Leverage the power of various Large Language Models that can be run locally for enhanced privacy and control.

⚙️ Framework & Developer Experience

Open Source & Free Forever

Access and utilize the entire framework under an open-source license, free of charge for continuous use.

Developer-Ready Framework

Provides a comprehensive and ready-to-use framework designed for developers to build private AI applications.

Flexible API & UI Access

Query the system via an OpenAI API-like interface or interact using a user-friendly Gradio web application.

Out-of-the-Box Functionality

Get started quickly with a solution that works immediately, directly addressing common enterprise privacy needs.

Use Cases

Secure Internal Knowledge Base Querying

Organizations face the challenge of enabling employees to quickly access information from vast internal documents without compromising sensitive data privacy. PrivateGPT solves this by providing a 100% local and private AI agent that can 'chat with your docs,' offering instant, context-aware answers without any data leaving the enterprise environment.

Financial Services, Healthcare, Legal, GovernmentFor: Knowledge Workers, Legal Professionals, Compliance Officers, HR Teams

Private Sales & Business Development Intelligence

Sales and business development teams require rapid access to internal client data, product information, and market insights for effective engagement, but sharing this sensitive data with external AI services is often prohibited. PrivateGPT allows these teams to build custom AI assistants that securely query internal documents and proprietary data, enhancing pre-sales research and personalized outreach while maintaining full data control.

B2B SaaS, Enterprise Sales, TechnologyFor: Account Executives, Sales Development Representatives, Business Development Managers

On-Premise AI Application Development & Secure Testing

AI/ML engineers and developers need to build and test sophisticated LLM-powered applications, particularly those leveraging Retrieval Augmented Generation (RAG) with proprietary datasets. PrivateGPT provides a secure, open-source, and fully local environment, enabling teams to develop, test, and refine context-aware AI solutions and generate test cases without ever exposing sensitive code or data to external cloud APIs, while also ensuring GDPR compliance.

Software Development, Technology, Enterprise ITFor: AI/ML Engineers, Software Developers, QA Engineers, DevOps Teams

Customized Departmental AI Assistant Deployment

Enterprises struggle to implement AI solutions tailored to the unique operational needs of various departments (e.g., HR, Customer Service, Legal) while adhering to strict internal security and compliance policies. PrivateGPT enables organizations to configure multiple, specialized AI assistants for different business areas, each with its own prompts, document sources, and tools, deployed securely on-premise or in a private cloud with robust access management and audit capabilities.

Large Enterprise (Cross-Sector), Public SectorFor: Department Heads, IT Directors, Solution Architects, Business Analysts

Frequently asked questions

PrivateGPT is a production-ready AI project that allows you to ask questions about your documents using Large Language Models (LLMs), with complete privacy protection. The platform provides an API that extends the OpenAI API standard, enabling you to build private, context-aware AI applications. Importantly, PrivateGPT operates entirely locally—no data leaves your execution environment at any point, making it 100% private.

PrivateGPT enables you to interact with your documents through Retrieval Augmented Generation (RAG) technology. The system processes documents locally, retrieves relevant information, indexes content securely, and vectorizes text efficiently before analyzing user queries and providing contextualized responses without sharing external data.

You can connect advanced tools to your assistants, including document upload, image analysis, prompt suggestions, source references, and external search tools like Google Search and Webpage Search. Additional features include DataAnalyzer for advanced data processing and artifacts for generating documents, tables, and code.

The API follows and extends the OpenAI API standard, supporting both normal and streaming responses. This means if you can use OpenAI API in one of your tools, you can use your own PrivateGPT API instead with no code changes—and it's free for local setups.

PrivateGPT can be deployed on-premise (data center, bare metal) or in your private cloud (AWS, GCP, Azure). The platform is hosted in your own Azure environment, supporting role-based access management, data encryption, and audit logs.

Setting up PrivateGPT involves cloning the repository, installing required dependencies including the LLM model and embedding model, and configuring the settings.yaml file. You'll need to download language and embedding models, set up the vector database, and test the installation. The LLM model can be installed using the poetry add command, with options like the LLaMA model.

Different regions have different optimal configurations—European users often prefer Mistral-based models due to alignment with EU AI regulations, while North American implementations more commonly use Llama 3 derivatives. PrivateGPT comes with a default language model (gpt4all-j-v1.3-groovy), but you're free to experiment with others like Falcon 40B from HuggingFace.

PrivateGPT allows you to create multiple AI assistants targeted at specific departments or business areas. Each assistant can be configured with its own prompts, access to relevant document sources (RAGs), and specialized tools tailored to the department's needs—such as HR, customer service, or sales.

You can customize the user experience with your own labels, welcome messages, and access rights, ensuring the platform matches your organizational structure and security requirements.

You can set up your own test environment (Testing App) where you can create, try out, and adjust assistants before making them available to the entire organization. This allows you to simulate user scenarios, review chat logs, and collect feedback to ensure quality and relevance before broad rollout.

PrivateGPT achieves privacy through a combination of local processing, zero external connections, and optional encryption—creating multiple layers of protection for sensitive data. You control who has access to which data and functions, and the platform can be configured to follow your company's own policies for data storage, access, and deletion.

The solution is designed to support GDPR and other relevant compliance requirements.

PrivateGPT can assist with test case generation, natural language processing testing, documentation creation, bug reporting, and user scenario simulation. It helps teams test various AI models while managing costs effectively and facilitating prompt sharing across teams.

PrivateGPT is designed to be adapted to your specific business processes and workflows, enabling you to create apps and AI assistants targeted at different departments or tasks.

Tags

natural language processingdata privacyretrieval augmented generationlocal llmprivate llm

Specifications

Deployment
Browser
API
Self-hosted
Target Audience
Individual
Startup
Enterprise
Complexity
Developer

Integrations

Zylon
Qdrant
LlamaIndex
OpenAI API
LangChainAI

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