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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Proactive AI Assistants Don't Wait for Commands - They Anticipate What You Need

Fazm Team·March 17, 2026·2 min read

proactiveai-assistantanticipationknowledge-graphhabits

Every AI assistant today works the same way. You ask a question, it answers. You give a command, it executes. The entire interaction model is reactive - the agent sits idle until you tell it what to do. This is like having an assistant who watches you struggle to find a document for ten minutes and only helps when you explicitly ask "where's the Q4 report?"

A useful human assistant would have already pulled it up because they noticed the meeting on your calendar.

From Reactive to Proactive

Proactive assistance requires two things - a knowledge graph of your patterns and the judgment to act on them without being annoying. The knowledge graph part is about observation. The agent watches when you open certain files, who you communicate with before specific meetings, what information you gather for recurring tasks.

Over time, patterns emerge. Every Monday at 9am you open the sales dashboard, pull three reports, and compile a summary email. Every time a meeting with a specific client appears on your calendar, you review their account history first. These aren't things you'd think to tell an agent. They're habits so automatic you barely notice them yourself.

The Judgment Challenge

The hard part isn't detecting patterns - it's knowing when to act. A proactive agent that surfaces irrelevant suggestions becomes noise. One that pre-loads the wrong documents wastes screen space. The agent needs confidence thresholds - only acting when it's highly certain the preparation will be useful.

This is why local-first matters for proactive agents. The observation needed to build accurate habit models requires deep access to your daily workflow. Sending all of that behavioral data to a cloud service is a non-starter for most people. An agent running locally can observe everything while keeping that intimate knowledge of your habits entirely on your machine.

The best assistant isn't the one that responds fastest. It's the one that has the answer ready before you ask the question.

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

Proactive AI Assistants Don't Wait for Commands - They Anticipate What You Need

From Reactive to Proactive

The Judgment Challenge

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