How much time will I actually save with Fazm?

Most users report saving 45-90 minutes per day on repetitive tasks. The biggest time savings come from email management (drafting replies, sorting, archiving), form filling (expense reports, CRM updates, applications), research (comparing products, gathering data from multiple sites), and social media (cross-posting, scheduling, replying). For example, booking a flight that normally takes 10 minutes of clicking through airline sites takes a single voice command with Fazm. Filing an expense report that requires opening a PDF, extracting numbers, and entering them into a spreadsheet becomes one spoken sentence. The more repetitive and multi-step your daily work is, the more time you get back.

What exactly can Fazm control?

Fazm controls everything you can do manually on your Mac. That includes mouse movements and clicks, keyboard typing, browser navigation and form filling, app switching, file management in Finder, and system-level actions. It uses direct browser DOM control for web interactions - meaning it reads and manipulates the actual page structure rather than taking screenshots and guessing where to click. For native macOS apps, Fazm uses accessibility APIs to interact with buttons, menus, text fields, and other UI elements. This works across any application: Chrome, Safari, VS Code, Slack, Figma, Terminal, Mail, Calendar, and more.

How is Fazm different from ChatGPT or Claude?

Chatbots like ChatGPT and Claude give you answers in a conversation window. Fazm takes action directly on your computer. When you say 'reply to Sarah's email,' Fazm opens your email app, finds Sarah's message, writes a contextual reply, and sends it. A chatbot would tell you what to write, but you still have to do all the clicking and typing yourself. Fazm moves your mouse, types on your keyboard, clicks buttons, and navigates between apps. It is a computer agent, not a chat assistant.

How does the memory layer work?

Fazm builds a personal knowledge graph by extracting information from your files, browsing history, conversations, and daily activity. Over time, it learns your contacts (names, emails, relationships), accounts and credentials, preferences (formatting, tone, scheduling habits), and frequently used workflows. In your first week, you might say 'Reply to Sarah's email, she's my cofounder, her email is sarah@acme.com.' By week four, you just say 'Reply to Sarah' because Fazm already knows who she is. By week eight, Fazm can draft the reply before you even ask. All of this data stays locally on your Mac - your knowledge graph never leaves your machine or gets sent to any cloud service.

Is Fazm safe? Can it mess up my computer?

Safety is built into every layer of Fazm. You watch every action in real-time on your screen - Fazm moves your mouse and types visibly, so there is nothing hidden. You can stop any action at any point by pressing a keyboard shortcut. Fazm also shows you what it plans to do before executing destructive actions like deleting files or sending emails, giving you a chance to confirm or cancel. Because Fazm is open source, the code is fully auditable on GitHub. There is no hidden behavior, no background processes making changes you cannot see, and no actions that bypass your screen.

What platforms does Fazm support?

Fazm currently supports macOS, running natively on both Apple Silicon (M1, M2, M3, M4) and Intel Macs. It is built with Swift and uses macOS-specific frameworks like ScreenCaptureKit for screen analysis and Accessibility APIs for app control, which is why macOS is the primary platform. Windows and Linux support are on the roadmap but do not have release dates yet. You can also control your Mac remotely from your phone using Fazm Remote, which gives you voice access to your desktop while you are away from your computer.

How does Fazm voice input work?

One keyboard shortcut activates push-to-talk. Hold the key, speak naturally about what you need done, and release. Fazm transcribes your speech locally using on-device models, so there is no network latency for the voice recognition step. You do not need wake words like 'Hey Siri' or 'OK Google' - just press and talk. You can also type commands into the floating toolbar if you prefer text input. Fazm understands natural language, so you do not need to memorize specific commands. Say 'book me a flight to Tokyo next Thursday' or 'find the cheapest AirPods on Amazon' and Fazm figures out the steps.

Is my data sent to the cloud?

Fazm processes screen analysis and memory entirely on your machine. The personal knowledge graph, file indexing, and screen capture all run locally. The only data that leaves your Mac is the intent - a text description of what you want to accomplish, which is sent to the AI model (Claude or GPT) for action planning. Your actual screen content, file contents, browsing history, and personal knowledge graph never leave your computer. Fazm is also open source, so you can verify exactly what data is transmitted by reading the code on GitHub. For users who need complete air-gapped operation, local model support is planned.

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Why Native Swift Menu Bar Apps Are the Right UI for AI Agents

Fazm Team·March 11, 2026·2 min read

swiftmacosui-designmenu-bardesktop-agent

Why Native Swift Menu Bar Apps Are the Right UI for AI Agents

Most AI tools make you switch to a separate window. Open ChatGPT. Open Claude. Open a dedicated app. Context switch, type your question, get your answer, switch back.

For a desktop agent that is supposed to save you time, this interaction model defeats the purpose. If you have to leave your current app to use the agent, you already lost the flow state you were trying to protect.

The Menu Bar Pattern

A floating bar that stays on top of your screen, activated by a keyboard shortcut (Option+Space), is the right pattern. It is:

Always available. No app-switching. No window hunting. No Cmd+Tab.
Never in the way. It appears when you need it and disappears when you do not.
Context-aware. Because it is a native app, it can see what app you are using and what is on screen.

Push-to-Talk Over Chat

The second insight is that voice input beats typing for agent interaction. If you are going to use an AI agent to control your computer, typing instructions into a chat box means your hands are busy doing something the agent should be handling.

Push-to-talk solves this: hold the hotkey, say what you need, release. The agent transcribes your speech locally and executes the actions. Your hands are free the entire time.

This is the difference between a transcription tool (like Whisper Flow) and a desktop agent. Transcription tools convert speech to text. Desktop agents convert speech to actions - the agent actually controls your mouse, keyboard, and applications to complete the task.

Why Native Swift Matters

Building this as a native Swift/SwiftUI app instead of an Electron wrapper matters for three reasons:

System integration. Native apps can use ScreenCaptureKit, accessibility APIs, and the Keychain directly. Electron apps need to go through Node.js bindings that are often incomplete or buggy.
Performance. A menu bar app needs to be instant. Sub-100ms activation time. Electron cannot deliver this consistently.
Resource usage. A floating overlay that runs all day cannot afford to consume 500MB of RAM. Native Swift apps typically use 30-50MB.

Fazm uses a native Swift menu bar interface with push-to-talk voice control. Open source on GitHub. Discussed in r/macapps.

Why Native Swift Menu Bar Apps Are the Right UI for AI Agents

Why Native Swift Menu Bar Apps Are the Right UI for AI Agents

The Menu Bar Pattern

Push-to-Talk Over Chat

Why Native Swift Matters

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What We Learned Building a macOS AI Agent in Swift (ScreenCaptureKit, Accessibility APIs, Async Pipelines)

Building a macOS Desktop Agent with Claude - How AI Wrote Most of Its Own Code

How LLMs Can Control Your Computer - Voice-Driven, Local, No API Keys