Dayflow is a private, automatic timeline of your day.
Stop guessing where your time went. Dayflow watches your screen and builds a detailed timeline of your day. Private and open‑source. Nothing leaves your Mac.

Quickstart • Why Dayflow • How people get value • Features • How it works • Installation • Data & Privacy • Automation • Debug & Developer Tools • Contributing

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What is Dayflow?

Dayflow is a native macOS app (SwiftUI) that watches your screen, analyzes it with AI, and generates a timeline of your activities with summaries. It's lightweight (25MB app size) and uses ~100MB of RAM and <1% cpu.

Privacy‑minded by design: You choose your AI provider. Use Gemini (bring your own API key), local models (Ollama / LM Studio), or ChatGPT/Claude (requires paid subscription). See Data & Privacy for details.

Why Dayflow

Most time trackers only log app usage. Dayflow understands context - the difference between "researching on YouTube" and "watching cat videos" - so your timeline reflects real work, not just which window was open.

It's fully open‑source and extensible: inspect the codebase, audit how data is handled, and build it yourself for maximum security.

How people get value

• Founders: See where days disappear, balance maker vs. manager time, and spot hidden context switching.
• Engineers: Verify what really shipped, generate a standup recap in minutes, and reduce interruption drag.
• Students: Make study sessions visible, reduce distraction drift, and build better routines.
• AI researchers: See where time actually went across experiments vs. reading vs. coding, and tighten your research loop.
• Marketing: Track time by campaign/channel, protect creative blocks, and cut hidden ops overhead.
• Sales: Make calls, follow‑ups, and CRM time visible; prep pipeline recaps fast.
• Freelancers: Generate client‑ready summaries, show proof of work, and catch scope creep early.

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Features

• Automatic timeline of your day with concise summaries.
• Context‑aware tracking - more than app usage; understands what you were doing.
• Extraordinarily battery‑efficient by design - stays out of your way.
• Watch timelapses of your day.
• Distraction highlights to see what pulled you off‑task.
• Timeline export - export your timeline as Markdown for any date range.
• Local‑first privacy - data stays on your Mac; choose your AI provider.
• Open‑source & extensible - inspect the codebase or build it yourself.
• Native UX built with SwiftUI.
• Automatic storage cleanup with configurable limits.

Daily Journal BETA

Set intentions, reflect on your day, and get AI-generated summaries of your activity.

• Morning intentions - plan what you want to accomplish.
• Evening reflections - review how your day actually went.
• AI summaries - get auto-generated insights from your timeline.
• Scheduled reminders - configurable notifications for intentions and reflections.
• Weekly view - see patterns across your week.

Note: Journal is currently in beta with limited access. Enter your access code in the app to unlock it.

Coming soon

• Dashboard (beta - ChatGPT/Claude only) - ask any question about your workday, pipe the answers into tiles you arrange yourself, and track trends over time.

  

How it works

1. Capture - Watches your screen in lightweight chunks.
2. Analyze - Periodically sends recent activity to your chosen AI provider.
3. Generate - AI creates timeline cards with activity summaries.
4. Display - Shows your day as a visual timeline.
5. Cleanup - Auto-manages storage based on your configured limits (1GB–20GB or unlimited).

AI Processing Pipeline

The efficiency of your timeline generation depends on your chosen AI provider:

flowchart LR
    subgraph Gemini["Gemini Flow: 2 LLM Calls"]
        direction LR
        GV[Video] --> GU[Upload + Transcribe<br/>1 LLM call] --> GC[Generate Cards<br/>1 LLM call] --> GD[Done]
    end

    subgraph Local["Local Flow: 33+ LLM Calls"]
        direction LR
        LV[Video] --> LE[Extract 30 frames] --> LD[30 descriptions<br/>30 LLM calls] --> LM[Merge<br/>1 call] --> LT[Title<br/>1 call] --> LC[Merge Check<br/>1 call] --> LMC[Merge Cards<br/>1 call] --> LD2[Done]
    end

    subgraph ChatCLI["ChatGPT/Claude Flow: 4-6 LLM Calls"]
        direction LR
        CV[Video] --> CE[Extract frames<br/>every 60s] --> CB[Batch describe<br/>10 frames/call] --> CM[Merge segments<br/>1 call] --> CC[Generate Cards<br/>1 call] --> CD[Done]
    end

    %% Styling
    classDef geminiFlow fill:#e8f5e8,stroke:#4caf50,stroke-width:2px
    classDef localFlow fill:#fff8e1,stroke:#ff9800,stroke-width:2px
    classDef chatcliFlow fill:#e3f2fd,stroke:#1976d2,stroke-width:2px
    classDef geminiStep fill:#4caf50,color:#fff
    classDef localStep fill:#ff9800,color:#fff
    classDef chatcliStep fill:#1976d2,color:#fff
    classDef processing fill:#f5f5f5,stroke:#666
    classDef result fill:#e3f2fd,stroke:#1976d2

    class Gemini geminiFlow
    class Local localFlow
    class ChatCLI chatcliFlow
    class GU,GC geminiStep
    class LD,LM,LT,LC,LMC localStep
    class CB,CM,CC chatcliStep
    class GV,LV,LE,CV,CE processing
    class GD,LD2,CD result

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Gemini leverages native video understanding for direct analysis. Local models reconstruct understanding from individual frame descriptions. ChatGPT/Claude uses CLI tools to batch-process extracted frames with frontier reasoning models - balancing quality and efficiency.

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Quickstart

Download (end users)

1. Grab the latest Dayflow.dmg from GitHub Releases.
2. Open the app; grant Screen & System Audio Recording when prompted:
   macOS → System Settings → Privacy & Security → Screen & System Audio Recording → enable Dayflow.

Build from source (developers)

1. Install Xcode 15+ and open Dayflow.xcodeproj.
2. Run the Dayflow scheme on macOS 13+.
3. In your Run scheme, add your GEMINI_API_KEY under Arguments > Environment Variables (if using Gemini).

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Installation

Requirements

• macOS 13.0+
• Xcode 15+
• A Gemini API key (if using Gemini): https://ai.google.dev/gemini-api/docs/api-key

From Releases

1. Download Dayflow.dmg and drag Dayflow into Applications.
2. Launch and grant the Screen & System Audio Recording permission.

From source

git clone https://github.com/JerryZLiu/Dayflow.git
cd Dayflow
open Dayflow.xcodeproj
# In Xcode: select the Dayflow target, configure signing if needed, then Run.

Homebrew

If you are using Homebrew, you can install Dayflow with:

$ brew install --cask dayflow

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Data & Privacy

This section explains what Dayflow stores locally, what leaves your machine, and how provider choices affect privacy.

Data locations (on your Mac)

All Dayflow data is stored in: ~/Library/Application Support/Dayflow/

• Recordings (video chunks): Dayflow/recordings/ (or choose "Open Recordings..." from the Dayflow Taskbar Icon Menu)
• Local database: Dayflow/chunks.sqlite
• Recording details: Lightweight screen capture, analyzed periodically, configurable storage limits
• Purge / reset tip: Quit Dayflow. Then delete the entire Dayflow/ folder to remove recordings and analysis artifacts. Relaunch to start fresh.

Processing modes & providers

• Gemini (cloud, BYO key) - Dayflow sends batch payloads to Google's Gemini API for analysis.
• Local models (Ollama / LM Studio) - Processing stays on‑device; Dayflow talks to a local server you run.
• ChatGPT / Claude (CLI-based, paid plan required) - Dayflow drives the Codex CLI (ChatGPT) or Claude Code CLI directly on your Mac. Requires an active ChatGPT Plus/Pro or Claude Pro subscription. Uses frontier reasoning models for best-in-class narrative quality.

TL;DR: Gemini data handling (my reading of Google’s ToS)

• Short answer: There is a way to prevent Google from training on your data. If you enable Cloud Billing on at least one Gemini API project, Google treats all of your Gemini API and Google AI Studio usage under the “Paid Services” data‑use rules - even when you’re using unpaid/free quota. Under Paid Services, Google does not use your prompts/responses to improve Google products/models.
  • Terms: “When you activate a Cloud Billing account, all use of Gemini API and Google AI Studio is a ‘Paid Service’ with respect to how Google Uses Your Data, even when using Services that are offered free of charge.” (Gemini API Additional Terms)
  • Abuse monitoring: even under Paid Services, Google logs prompts/responses for a limited period for policy enforcement and legal compliance. (Same Terms)
  • EEA/UK/Switzerland: the Paid‑style data handling applies by default to all Services (including AI Studio and unpaid quota) even without billing. (Same Terms)

A couple useful nuances (from docs + forum clarifications):

• AI Studio is still free to use; enabling billing changes data handling, not whether Studio charges you. (Pricing page)
• UI “Plan: Paid” check: In AI Studio → API keys, you’ll typically see “Plan: Paid” once billing is enabled on any linked project (UI may evolve).
• Free workaround: “Make one project paid, keep using a free key elsewhere to get the best of both worlds.” The Terms imply account‑level coverage once any billing account is activated, but the Apps nuance above may limit this in specific UI contexts. Treat this as an interpretation, not legal advice.

Local mode: privacy & trade‑offs

• Privacy: With Ollama/LM Studio, prompts and model inference run on your machine. LM Studio documents full offline operation once models are downloaded.
• Quality/latency: Local open models are improving but can underperform cloud models on complex summarization.
• Power/battery: Local inference is GPU‑heavy on Apple Silicon and will drain battery faster; prefer plugged‑in sessions for long captures.
• Future: We may explore fine‑tuning or distilling a local model for better timeline summaries.

References:

• LM Studio offline: https://lmstudio.ai/docs/app/offline
• Ollama GPU acceleration (Metal on Apple): https://github.com/ollama/ollama/blob/main/docs/gpu.md

ChatGPT/Claude mode: privacy & trade‑offs

• Privacy: Your screen data is processed by OpenAI (ChatGPT) or Anthropic (Claude) depending on which CLI you configure. Review their respective privacy policies.
• Quality: Frontier reasoning models provide the highest quality narratives and summaries.
• Subscription required: You must have an active paid subscription (ChatGPT Plus/Pro at $20+/month, or Claude Pro at $20/month). The CLI tools authenticate through your existing subscription.
• Setup: Requires installing the Codex CLI or Claude Code and staying signed in.
• Internet: Requires an active internet connection (no offline mode).

Permissions (macOS)

To record your screen, Dayflow requires the Screen & System Audio Recording permission. Review or change later at:
System Settings → Privacy & Security → Screen & System Audio Recording.
Apple’s docs: https://support.apple.com/guide/mac-help/control-access-screen-system-audio-recording-mchld6aa7d23/mac

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Configuration

• AI Provider
  • Choose Gemini (set API key), Local (Ollama/LM Studio), or ChatGPT/Claude (install CLI + paid subscription).
  • For Gemini keys: https://ai.google.dev/gemini-api/docs/api-key
  • For ChatGPT: Install Codex CLI, sign in with your ChatGPT Plus/Pro account
  • For Claude: Install Claude Code, sign in with your Claude Pro account
• Capture settings
  • Start/stop capture from the main UI. Use Debug to verify batch contents.
• Data locations
  • See Data & Privacy for exact paths and a purge tip.

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Automation

Dayflow registers a dayflow:// URL scheme so you can trigger common actions from Shortcuts, hotkey launchers, or scripts.

Supported URLs

• dayflow://start-recording - enable capture (no-op if already recording)
• dayflow://stop-recording - pause capture (no-op if already paused)

Quick checks

• From Terminal: open dayflow://start-recording or open dayflow://stop-recording
• In Shortcuts: add an Open URLs action with either link above

Deeplink-triggered state changes are logged as reason: "deeplink" in analytics so you can distinguish automations from manual toggles.

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Debug & Developer Tools

You can click the Dayflow icon in the menu bar and view the saved recordings

Project structure

Dayflow/
├─ Dayflow/                 # SwiftUI app sources (timeline UI, debug UI, capture & analysis pipeline)
├─ docs/                    # Appcast and documentation assets (screenshots, videos)
├─ scripts/                 # Release automation (DMG, notarization, appcast, Sparkle signing, one-button release)

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Troubleshooting

• Screen capture is blank or fails
  Check System Settings → Privacy & Security → Screen & System Audio Recording and ensure Dayflow is enabled.
• API errors
  Go into settings and verify your GEMINI_API_KEY and network connectivity.

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Roadmap

• V1 of the Dashboard (track answers to custom questions)
• V1 of the daily journal - now in beta!
• Fine-tuning a small VLM for improved local model quality

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Contributing

PRs welcome! If you plan a larger change, please open an issue first to discuss scope and approach.

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License

Licensed under the MIT License. See LICENSE for the full text. Software is provided “AS IS”, without warranty of any kind.

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Acknowledgements

• Sparkle for battle‑tested macOS updates.
• Google AI Gemini API for analysis.
• Ollama and LM Studio for local model support.
• OpenAI Codex CLI and Claude Code for CLI-based inference.