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LocalGPT
LocalGPT is a fully private, on-premise document intelligence platform featuring a hybrid search engine and a smart router for advanced Retrieval-Augmented Generation (RAG) and direct LLM answering.
AI Tool
private-gpt Review
PrivateGPT is an open-source API layer for building private, context-aware AI applications with local models, ensuring data privacy.
shipped Jun 10, 2026aifreemium
1PrivateGPT is an open-source API layer designed for building private AI applications that operate entirely within a user's environment.
2It ensures 100% data privacy and sovereignty by connecting to OpenAI-compatible inference servers locally, preventing data from leaving the user's environment.
3The project has garnered significant community interest, accumulating over 57,000 stars and 8,000+ forks on GitHub.
4Developed by Zylon.ai, PrivateGPT supports compliance standards such as HIPAA and SOC 2 through its on-premise deployment model.
private-gpt at a Glance
About private-gpt
Leadership
Iván Martínez ToroCo-founder
Daniel Gallego VicoCo-founder
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2
Jan.ai
Jan.ai is an open-source, local-first AI platform that enables users to run various Large Language Models (LLMs) directly on their computer, guaranteeing data privacy by keeping all processing offline.
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OnPrem.LLM
OnPrem.LLM is a Python-based toolkit designed for applying LLMs to sensitive, non-public data in offline or restricted environments, complete with prebuilt pipelines for document processing and RAG.
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LM Studio
LM Studio is a user-friendly desktop application that simplifies the process of downloading, managing, and running a wide range of local LLMs, ensuring all data processing remains on the user's device.
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overview
What is private-gpt?
private-gpt is an open-source API layer tool developed by Zylon.ai that enables developers and organizations with privacy-sensitive data to build private, context-aware AI applications using local models. It ensures no data leaves their environment by connecting to any OpenAI-compatible inference server. PrivateGPT functions as a local AI application layer, providing essential building blocks for creating private AI products without running Large Language Models (LLMs) itself. Instead, it interfaces with any OpenAI-compatible inference server that implements /v1/chat/completions and /v1/models endpoints, such as Ollama, llama.cpp, or vLLM. This architecture is critical for maintaining strict data control and privacy, particularly in regulated sectors like finance, healthcare, defense, and government, where data sovereignty is a non-negotiable requirement. Key functionalities include enabling generative AI capabilities for context-aware applications, facilitating private knowledge management through secure internal chatbots, and automating document-heavy tasks in legal sectors by analyzing and summarizing documents locally. The platform provides developers with an API layer to construct private AI solutions without the necessity of re-engineering backend primitives or relying on external cloud APIs.
quick facts
Quick Facts
| Attribute | Value |
|---|---|
| Developer | Zylon.ai |
| Business Model | Open Source / Freemium |
| Pricing | Free (open-source core) |
| Platforms | Web, API |
| API Available | Yes |
| Founded | 2023 |
| HQ | New York, USA |
| Funding | Bootstrapped, $3.2M |
features
Key Features of private-gpt
PrivateGPT provides a robust set of features designed for building secure, local AI applications, emphasizing data privacy and developer control.
- 1Open-source API layer for private AI application development.
- 2Supports local or self-hosted model servers, ensuring data remains within the user's environment.
- 3Claude API-compatible for seamless integration with various inference servers.
- 4Provides essential building blocks for AI applications, including messages, ingestion, retrieval, and tool use.
- 5Enables Retrieval-Augmented Generation (RAG) pipelines for private document interaction.
- 6Ensures 100% data privacy and sovereignty, with no data leaving the user's environment.
- 7Supports various vector databases, including Milvus and Clickhouse (as of v0.6.0).
- 8Compatible with OpenAI-compatible inference servers like Ollama, llama.cpp, and vLLM.
- 9Offers 'Recipes,' which are high-level APIs for AI-native use cases, such as the `summarize` function introduced in v0.6.0.
- 10Supports Gemini (LLM and Embeddings) as of Version 0.6.0.
use cases
Who Should Use private-gpt?
PrivateGPT is tailored for specific user groups and organizations that prioritize data privacy, control, and local operation in their AI application development.
- 1**Developers:** For building custom, private, context-aware AI applications without dependencies on cloud APIs or external data processing.
- 2**Platform Teams:** For integrating advanced AI capabilities like file ingestion, retrieval, and tool use into existing systems while maintaining strict data control and sovereignty.
- 3**Organizations with Privacy-Sensitive Data:** For ensuring 100% data privacy and sovereignty when interacting with internal documents and knowledge bases using AI.
- 4**Businesses in Regulated Industries (Financial, Healthcare, Government sectors):** For meeting stringent compliance requirements such as HIPAA and SOC 2 by keeping all data processing on-premise and within their controlled environment.
- 5**Teams requiring Private Knowledge Management:** For creating internal chatbot-like interfaces that securely leverage company-specific knowledge bases without exposing sensitive information to third-party cloud providers.
pricing
private-gpt Pricing & Plans
PrivateGPT operates on a freemium model, with its core being an open-source project available for free. The open-source version provides 100% privacy, supports local or self-hosted model servers, is Claude API-compatible, and includes essential building blocks for AI applications without data leaks. For enterprise-grade deployments and additional features, Zylon.ai, the maintainer of PrivateGPT, offers a commercial platform named Zylon. This enterprise platform is built on PrivateGPT and includes an integrated inference server, Kubernetes deployment, API gateway, user management, and audit logs. Specific pricing details for the Zylon enterprise offering are not publicly detailed, as they typically involve custom agreements based on organizational needs.
- 1Open-source / Free: Free (Includes 100% privacy, local/self-hosted model server, Claude API-compatibility, essential building blocks, no data leaks)
competitors
private-gpt vs Competitors
PrivateGPT occupies a distinct niche by prioritizing local, private AI application development, differentiating itself from both cloud-based AI services and other open-source projects.
1
LocalGPT is a fully private, on-premise document intelligence platform featuring a hybrid search engine and a smart router for advanced Retrieval-Augmented Generation (RAG) and direct LLM answering.
Similar to private-gpt, LocalGPT prioritizes 100% private, local document interaction, ensuring no data leaves the user's machine. It offers a more sophisticated RAG system with hybrid search and a web interface, providing a more comprehensive end-user solution.
2
Jan.ai↗
Jan.ai is an open-source, local-first AI platform that enables users to run various Large Language Models (LLMs) directly on their computer, guaranteeing data privacy by keeping all processing offline.
Like private-gpt, Jan.ai emphasizes local execution and privacy with no data leaving the device. It provides a user-friendly desktop application for Windows, macOS, and Linux, supporting a growing library of open-source models for a more accessible experience.
3
OnPrem.LLM is a Python-based toolkit designed for applying LLMs to sensitive, non-public data in offline or restricted environments, complete with prebuilt pipelines for document processing and RAG.
While private-gpt is a specific application for document Q&A, OnPrem.LLM serves as a more extensive toolkit for developers and organizations to build privacy-focused document AI solutions. It offers greater flexibility and a broader array of document intelligence features, including information extraction and summarization.
4
LM Studio is a user-friendly desktop application that simplifies the process of downloading, managing, and running a wide range of local LLMs, ensuring all data processing remains on the user's device.
LM Studio provides a graphical user interface for easy management and interaction with local LLMs, similar to private-gpt's local interaction capabilities. Its primary strength lies in its ease of use for discovering and running diverse models, offering a more generalized local LLM experience compared to private-gpt's document-centric focus.
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Frequently Asked Questions
+What is private-gpt?
private-gpt is an open-source API layer tool developed by Zylon.ai that enables developers and organizations with privacy-sensitive data to build private, context-aware AI applications using local models. It ensures no data leaves their environment by connecting to any OpenAI-compatible inference server.
+Is private-gpt free?
Yes, private-gpt is an open-source project available for free, offering 100% privacy and local operation. Zylon.ai, the maintainer, also offers an enterprise platform built on PrivateGPT with additional features, though specific pricing for this commercial offering is not publicly detailed.
+What are the main features of private-gpt?
private-gpt's main features include its open-source API layer for private AI applications, support for local or self-hosted model servers, Claude API-compatibility, and essential building blocks for messages, ingestion, retrieval, and tool use. It enables Retrieval-Augmented Generation (RAG) pipelines for secure document interaction and ensures 100% data privacy.
+Who should use private-gpt?
private-gpt is primarily designed for developers, platform teams, and organizations handling privacy-sensitive data, especially those in regulated industries like finance, healthcare, and government. It enables them to build context-aware AI applications and interact with documents privately without relying on cloud API dependencies.
+How does private-gpt compare to alternatives?
Compared to alternatives, private-gpt distinguishes itself by offering an API layer for building private, document-centric AI applications with 100% local data processing. Unlike LocalGPT or Jan.ai which offer more comprehensive end-user solutions or desktop applications, private-gpt focuses on providing core building blocks for developers. It prioritizes data sovereignty over cloud-based AI services like ChatGPT.
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