All Open Source Apps

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

Define, schedule, and monitor complex data workflows as Python code — with a powerful UI, 80+ provider integrations, and battle-tested scalability across thousands of production deployments.

Open-source ELT platform with 600+ connectors for moving data from any source to warehouses, lakes, and AI agents.

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

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

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.

Build enterprise-grade AI agents with RAG, workflows & multi-modal support

Redash lets anyone connect to 35+ SQL and NoSQL data sources, write a query in the browser, and turn the result into a shared dashboard — no separate BI suite required.

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

Open-source GenBI engine that lets AI agents turn natural-language questions into governed SQL, charts, and shareable dashboards across 20+ data sources — no vendor lock-in, no black-box prompts.

A reactive Python notebook that eliminates hidden state, runs reproducibly, and deploys as a web app or script — stored as pure Python, built for the AI era.

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.

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

The open-source API layer that turns local LLMs into production private AI applications with full Claude API compatibility

A Microsoft-built training framework that optimizes AI agents with reinforcement learning, automatic prompt optimization, or supervised fine-tuning — with near-zero code changes to your existing agent, in any framework.

Give your LLM agents on-the-job training—ART lets you apply GRPO reinforcement learning to any multi-step agentic workflow with minimal code changes.

Compress everything your AI agent reads — tool outputs, logs, RAG chunks, and files — before it reaches the LLM, achieving 60–95% fewer tokens with the same answers.

An open-source context database that gives AI agents a unified filesystem for memory, resources, and skills with hierarchical tiered retrieval.

Local-first AI memory with verbatim storage, pluggable backends, and 96.6% retrieval recall on LongMemEval — no API key required.

Drop your files and search them instantly — no vector DB, no indexing pipeline, just raw data queried by a self-evolving intelligence layer.

Visual ETL that compiles to Polars — build pipelines on a canvas, export as standalone Python, and run anywhere without platform lock-in.

Transform messy, unstructured documents into persistent, navigable memory that AI agents can actually use.

A self-hosted, OpenAI-compatible LLM gateway that puts one endpoint in front of 40+ providers, with virtual API keys, per-user budgets enforced before spend, and full usage tracking.

An all-in-one open-source training suite for finetuning diffusion models—FLUX, SDXL, Wan video, and audio—on consumer GPU hardware via CLI or web UI.