Self-Hosted AI Agents
Self-hosted agents ranked by verified user ratings.
Self-hosted AI agents run on your own infrastructure, so data never leaves your network and you control the model, updates, and access. The tradeoff is operational overhead. These agents are ranked by verified user ratings from teams running them in production.
AI agents
chat-ui
The open source codebase powering HuggingChat
h2ogpt
Private chat with local GPT with document, images, video, etc. 100% private, Apache 2.0. Supports oLLaMa, Mixtral, llama.cpp, and more. Demo: https://gpt.h2o.ai/ https://gpt-docs.h2o.ai/
hertzbeat
An AI-powered next-generation open source real-time observability system.
hermes-desktop
Desktop Companion for Hermes Agent
guardrails
Adding guardrails to large language models.
mistral-inference
Official inference library for Mistral models
langchain4j
LangChain4j is an idiomatic, open-source Java library for building LLM-powered applications on the JVM. It offers a unified API over popular LLM providers and vector stores, and makes implementing tool calling (including MCP support), agents and RAG easy. It integrates seamlessly with enterprise Java frameworks like Quarkus and Spring Boot.
bitsandbytes
Accessible large language models via k-bit quantization for PyTorch.
peft
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
botpress
The open-source hub to build & deploy GPT/LLM Agents ⚡️
rowboat
Open-source AI coworker, with memory
parlant
Build reliable customer-facing AI agents with Parlant: an interaction control harness optimized for controlled, consistent, and predictable LLM interactions.
Frequently asked questions
What is a self-hosted AI agent?
A self-hosted AI agent runs on infrastructure you control, such as your own cloud account or on-premise servers, rather than the vendor hosting it for you.
Why self-host an AI agent?
Teams self-host mainly for data privacy, compliance, cost control at scale, and the ability to customize or swap models.