All Open Source Apps

Stateful actors as a primitive for AI agents, real-time collaboration, and durable execution — with in-memory state, WebSockets, queues, and scheduling built in.

A local desktop hub that unifies SSH, Docker, Kubernetes, VMs, and remote desktops into one interface — no agents, no remote setup.

A graph-vector database built from scratch in Rust that unifies graph traversal, vector search, key-value, and relational storage into a single platform for AI applications.

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.

Secure, fast, and extensible sandbox runtime for AI agents with multi-language SDKs and Docker/Kubernetes runtimes.

The safe, private runtime that lets autonomous AI agents operate in sandboxed environments governed by declarative YAML policies — blocking data exfiltration, credential leaks, and unauthorized network activity before they happen.

The dbt-native data observability CLI that turns your existing dbt tests and metadata into anomaly detection, lineage graphs, and Slack/Teams alerts — no separate platform required.

A free, open source procedural 2D design tool that unifies vector, raster, motion graphics, and generative art in a single node-based nondestructive workflow.

Mesh LLM pools GPUs and memory across every machine you own into one OpenAI-compatible API, so agents tap distributed compute instead of a single GPU box or a metered cloud bill.

Open-source feedback management and roadmap tool that lets product teams collect, prioritize, and respond to user input — with AI-powered summarization and full self-hosting control.

A terminal-native agent multiplexer that runs Claude, Codex, Gemini, and other coding agents side by side in real, persistent panes you can detach from and reattach to from anywhere.

Open-source time-series database built for real-time ingest, fast SQL queries, and embedded Python automation — powered by Apache Arrow and Parquet.

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

A fast, lightweight, open-source document parser that extracts spatial text, bounding boxes, and Markdown from PDFs and Office files — entirely on your machine.

AI-powered file type detection that identifies 200+ content types with ~99% accuracy in milliseconds using a compact deep learning model.

A lightweight, stealthy headless browser written in Rust — drop-in compatible with Puppeteer and Playwright, built for AI agents and web scraping at scale.

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.

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

A pretrained decoder-only foundation model by Google Research that delivers zero-shot time series forecasting with calibrated quantile prediction intervals — no training required.

An open-source runtime control plane for AI agents — define safety guardrails once, apply them across agents built on LangChain, CrewAI, Google ADK, or AWS Strands, and update controls without redeploying code.

An open-source CLI that compiles raw documents into a structured, interlinked wiki-style knowledge base using LLMs — powered by vectorless, reasoning-based retrieval (PageIndex) instead of a vector database.

Turn AI-written code into real apps — an open-source, self-hostable backend with Database, Auth, Storage, Memory, Functions, Assets, AI Gateway, and cron built for AI coding agents.

Federated AI search and RAG across 100+ enterprise sources—no data extraction, no vector database required.