Open Source AI Development Apps

The open source AI engineering platform for debugging, evaluating, monitoring, and optimizing production LLMs and agents at scale.

The open-source hub for building and deploying LLM-powered AI agents with TypeScript-first tooling, 40+ integrations, and a revolutionary code-execution agent framework.

Build sophisticated chatbots visually, embed them anywhere without iframes, and own your data — fully self-hostable with a modular block system and 30+ integrations.

Build, run, and manage agent platforms with a full production stack — SDK, runtime, and control plane included.

Build, debug, and deploy knowledge-based AI agents with a visual workflow editor, RAG retrieval, and support for any OpenAI-compatible LLM.

Label Studio is an open-source, multi-type data labeling platform that lets teams annotate images, text, audio, video, and time series data with a configurable XML-based UI and export annotations in formats ready for any ML framework.

The most powerful node-based AI workflow engine for creating images, video, 3D models, and audio with full control over every generation step.

Visual LLM workflow platform with RAG pipelines, agent capabilities, and model management for building production AI applications.

Open source AI engineering platform for LLM observability, prompt management, evaluation, and debugging — self-host in minutes or use Langfuse Cloud.

Open source AI gateway and Python SDK that gives you one OpenAI-compatible interface to call 100+ LLM providers, with built-in routing, cost tracking, guardrails, and virtual keys.

The open source operating system and SDK that lets developers build one app and run it across smart glasses from Even Realities, Vuzix, Mentra Live, and more.

Open-source vector database and search engine built in Rust for production-grade AI applications — from semantic search to RAG pipelines and recommendation systems.

The open-source LLMOps platform unifying prompt engineering, evaluation, and observability for teams building reliable LLM applications.

An open-source CLI that packages machine learning models into standard, production-ready Docker containers — no Dockerfile wrangling, no CUDA version hell.

Drag-and-drop visual builder for AI agents, RAG pipelines, and multi-agent systems—deploy anywhere in minutes.