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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Building a Native Swift Voice App for macOS - Open Source Journey

Fazm Team·March 17, 2026·2 min read

swiftvoice-appmacosopen-sourcewhisperkit

Building a Native Swift Voice App for macOS - Open Source Journey

The idea is simple. You talk to your computer and it does things. Not "it shows you a chat response" - it actually opens apps, fills forms, sends messages, organizes files. A voice interface for your entire desktop.

Why Native Swift

Electron would have been faster to prototype. We went with native Swift anyway because desktop agents need low-latency access to system APIs that web wrappers cannot provide efficiently. Accessibility APIs for reading screen content. Core Audio for microphone access without browser permission dialogs. AppKit for window management. These are not nice-to-haves - they are the core functionality.

SwiftUI handles the interface - a minimal overlay that shows transcription status and agent actions. The UI stays out of the way because the whole point is that you should not need to look at a screen to control your computer.

WhisperKit for Local Transcription

Speech-to-text runs locally using WhisperKit, which is optimized for Apple Silicon. No audio leaves your machine. Transcription latency on an M1 is under 500ms for typical commands, which feels close to real-time.

Local transcription also means the app works offline and does not depend on any cloud service's uptime or pricing changes. The model runs on your hardware using your cores. That is it.

Accessibility APIs for Control

macOS accessibility APIs let the agent read what is on screen - button labels, text field contents, menu items - and interact with those elements programmatically. This is the same API that screen readers use, which means it works across virtually every macOS application without needing app-specific integrations.

The combination of voice input, local transcription, and accessibility-based control creates something that feels genuinely different from typing commands into a chat box. You say "send the weekly report to the team Slack channel" and watch it happen.

The entire project is open source because we believe desktop agents should be transparent about what they do on your machine.

Fazm is an open source macOS AI agent. Open source on GitHub.

Building a Native Swift Voice App for macOS - Open Source Journey

Building a Native Swift Voice App for macOS - Open Source Journey

Why Native Swift

WhisperKit for Local Transcription

Accessibility APIs for Control

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