Launching today
Freu AI
Automate any Mac app with $0 recurring run cost
32 followers
Automate any Mac app with $0 recurring run cost
32 followers
Freu AI is an AI agent for Mac that automates any desktop app with natural language. It “sees” your UI to compile a cross‑app workflow once, then runs it locally via a deterministic DSL—no brittle coordinates/selectors and no recurring token bills. Bonus: we’re open‑sourcing freu-cli (our browser automation engine) today.
Freu AI
Hi Product Hunt! 👋 I'm Charles, founder of Freu AI.
A while back, we teased that we were working on extending our browser automation tech to the entire operating system. Today, we are officially launching Freu AI for Mac—an AI agent that automates any desktop software across your OS using natural language.
The Problem: Vision Agents are Too Expensive & RPA is Too Brittle
We hit a massive wall with current GUI automation. Traditional RPA (AppleScript, rigid X/Y coordinate clickers) breaks the moment you resize a window or an app updates its UI. On the flip side, modern multimodal agents (sending screenshots to cloud LLMs) scale terribly for repetitive tasks.
Right now, most desktop agents operate like interpreters. Every time you ask it to "Extract data from this local PDF and enter it into Excel," it takes a screenshot, sends it to the cloud, reasons about the visual layout, and clicks.
The Traditional Cost: ~10k tokens (Image context) × 5 steps × 10 runs a day = ~500k tokens/day just to navigate the exact same desktop UI, not to mention the unbearable latency.
The Solution: AOT Compilation + Semantic UI (SUI)
Freu AI changes this by introducing Ahead-of-Time (AOT) compilation for OS-level tasks. Instead of the agent analyzing the screen from scratch every single time, you show it the cross-app workflow once.
Freu AI uses a cloud vision-based model to "compile" that session into a deterministic, reusable DSL.
The Freu Cost: You pay the cloud "AI reasoning" token cost once when the agent watches and learns your workflow. But for future runs? The agent simply invokes the pre-compiled DSL command locally. This drops your recurring execution costs to zero and reduces latency from minutes to seconds.
How it works under the hood:
When you record a desktop workflow, our engine doesn't just save a dumb macro. It uses Semantic UI (SUI) to understand the screen:
Perceive: It recognizes buttons, text fields, and icons across any app.
Resolve: It anchors to the semantic meaning of the UI, not rigid coordinates. If Spotify moves their "Play" button, Freu AI still finds it.
Execute: It binds these visual anchor points into our DSL and executes them deterministically.
🎁 The Open-Source Bonus:
While the Mac desktop app is our core product, we are open-sourcing freu-cli today—our underlying DOM-based browser automation engine. You can drop it into your own agents to give them instant "muscle memory" for web tasks. Repo here: https://github.com/freu-ai/freu-cli
🔮 What’s Next: The Local Vision Execution Engine
We are relentlessly upgrading our stack. Very soon, we will launch a capability to run the execution phase using a lightweight, SUI-optimized vision model running entirely locally on your hardware. While we will always rely on powerful cloud LLMs to understand your complex intent during the initial "learning" phase, this upcoming local engine means your day-to-day repetitive executions will cost exactly zero API tokens and keep your real-time screen data 100% private.
We’d love for you to try Freu AI for Mac. I’d love to hear your feedback on our AOT approach or how you're currently handling repetitive cross-app tasks. My co-founders and I will be hanging out in the comments all day to answer your questions! 🚀
Pretty simple but a very cool approach, also awaiting local vision engine!