Open Source AI Development Apps

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.

The self-hosted developer control center for running AI coding agents — locally, in Docker, on VMs, or across cloud backends — with automation workflows for GitHub, Slack, and more.

Open-source, embedded vector database built on the Lance columnar format for fast multimodal search across billions of vectors, backed by Y Combinator (W23).

Build, test, and deploy AI agents and RAG workflows visually with native API and MCP server export.

High-performance in-memory graph database for AI context and real-time analytics

An open-source CLI and library for evaluating and red-teaming LLM applications — replace trial-and-error prompt engineering with systematic evals, vulnerability scanning, and CI/CD integration.

Build and deploy fully-managed AI agents and background jobs in TypeScript — with no timeouts, durable retries, real-time observability, and elastic scaling built in.

Turn any website into clean, LLM-ready data with a single API call — no proxy headaches, no scraping complexity.

Git, but better — a modern version control client with stacked branches, parallel workflows, unlimited undo, and first-class support for AI-powered development.

Run and fine-tune LLMs, diffusion, audio and embedding models on your own hardware, from a native desktop app, a browser UI, or a Python library.

An open source AI-native proxy that secures, observes, and governs agent-to-LLM, agent-to-tool, and agent-to-agent communication through MCP, A2A, and unified LLM routing.

The batteries-included Python agent harness — planning, sub-agents, filesystem, shell, memory, and skills bundled in, built on LangGraph.

A Postgres-backed orchestration engine for background tasks, AI agents, and durable workflows that replaces Redis queues and multi-datastore durable execution platforms with a single self-hostable service.

Run LLM-generated Python code safely inside your agent—no containers, no CPython, no compromise—with sub-microsecond startup.