MultiAgentOS
New · Train your own private AI
Our flagship app, LLM Academy, lets anyone turn an open-source model into their own private AI specialist and run it on their own machine, with no code. Alongside it: a supervised desktop agent, an AI-drivable browser, a job-search assistant, and a coding tutor, all local-first.
The apps share a practical philosophy: visible automation, local control, useful defaults, and human approval before important actions.
See the runtime toolsSee it in action
The core tools are built around visible, interruptible workflows: browser sessions, desktop tasks, files, terminals, coding lessons, and job-search drafts.
Turn an open-source model into your own private AI specialist, right on your computer. A three-step, no-code Expert Builder, a full fine-tuning studio, a built-in model hub, and one-click export make training your own model genuinely approachable.
A native Avalonia desktop workspace for Mac and Windows. Chat with API providers, local servers, CLI tools, Terminal commands, OAuth providers, or local GGUF models, then supervise the LLM through browser, desktop, code, terminal, file, screenshot, and subagent sidecars.
A desktop browser built for humans and AI agents. Browse normally, or let an LLM navigate, click, fill forms, execute JavaScript, take screenshots, and report back through a visible bridge panel and local JSON-RPC/WebSocket server.
A desktop app for job seekers and recruiters. A real browser and an AI assistant sit side by side: find roles or candidates, draft tailored emails and cover letters from your CV or role brief, and send from your own inbox, only after you approve.
A fully local desktop app for learning to code with an AI tutor, built on the same Avalonia shell as MultiAgentOS. It pairs the full chat-and-sidecar workspace with structured language tracks, thousands of interactive lessons, multi-file coding projects, and a built-in glossary.
Bring cloud APIs, local servers, OAuth providers, terminal commands, or fully local model files. The software keeps those options visible instead of hiding them behind a black box.
Connect OpenAI, Anthropic, DeepSeek, xAI, Google, Mistral, and compatible providers.
Use Ollama, LM Studio, llama.cpp, GPT4All, vLLM, or your own compatible local server.
Route prompts through command line tools and collect their output inside the app.
Sign in to supported providers without scattering credentials around your system.
Let the software run supervised shell tasks when the job calls for it.
Point at GGUF model files and run offline where that workflow makes sense.
MultiAgentAI software is designed for repeatable tasks: browsing, code, terminal work, file handling, screenshots, language practice, application drafts, and supervised handoffs.
Local-first where possible, transparent when tools run, practical about model choice, and careful about what leaves your machine.
Your prompts, files, settings, and run history stay on your machine unless you choose a cloud provider.
Use API providers, local servers, terminal tools, or local GGUF models depending on the task.
Support the build, choose a product and platform, and receive a private installer link when builds are available.
Approval walls, visible sidecars, and stop controls keep the human in the loop.
Flagship product
Turn an open-source model into your own specialist with a no-code Expert Builder, fine-tune it with full control, then export it or serve it to your own tools, all on your own machine.
LLM Academy Expert Builder3 stepsGet the software
Give whatever you like, pick the app and your computer type, and download the installer after checkout when a build is published.
Software catalog
LLM Academy, MultiAgentOS with its Mac and Windows builds, LLM Browser, Jobomate, and Codemonkey AI are all part of the same practical software studio.
In development
Train your own private AI on your own machine. A no-code Expert Builder turns an open-source model into a specialist in three steps, with a full fine-tuning studio, a model hub, recipe templates, and one-click export to GGUF, LoRA, or a local API behind it.
Explore LLM Academy →
In development
MAOS Mac OS is the Apple Silicon and Intel build on the shared .NET / Avalonia shell. Secrets live in the macOS Keychain, desktop control runs through CGEvent / CoreGraphics, and a zero-setup bundled llama.cpp runtime means you can work fully offline.
Explore MAOS for Mac →
In development
MAOS Windows is the Windows 10 and 11 build on the shared .NET / Avalonia shell. Secrets live in Windows Credential Manager, the agent drives your desktop and PowerShell / Cmd, and five on-demand tool packs add executable diagnostics only when a task needs them.
Explore MAOS for Windows →
In development
A desktop browser built for humans and AI agents. Browse normally, or let an LLM navigate, click, fill forms, execute JavaScript, take screenshots, and report back through a visible bridge panel and local JSON-RPC/WebSocket server.
Explore LLM Browser →
In development
A desktop app for job seekers and recruiters: a real browser plus an AI assistant that finds roles or candidates, drafts tailored emails and cover letters from your CV or role brief, and sends from your own inbox, only after you approve.
Explore Jobomate →
In development
A fully local desktop app for learning to code with an AI tutor, built on the same Avalonia shell as MultiAgentOS. It pairs the full chat-and-sidecar workspace with 20 language tracks, 2,478 lessons across 12 interactive step kinds, multi-file coding projects, and an 88-entry glossary.
Explore Codemonkey AI →