Dayflow is a time-tracking and work journal tool that automatically reconstructs your workday from screen activity on macOS.
The problem Dayflow solves is the friction of manual time tracking and work logging. Rather than requiring timers or manual note-taking, it passively monitors screen activity and transforms that raw data into a chronological timeline of what you actually accomplished. The tool then surfaces this information through multiple views: an automatic timeline, a daily standup summary with priorities and blockers, a weekly review showing focus patterns and time allocation, and a chat interface that lets you query your work history with natural language questions grounded in your actual activity data.
Dayflow is built for developers and knowledge workers who want accountability and retrospective clarity without the overhead of active logging. It suits anyone who struggles to remember what they did during the day or who needs to prepare standups and status updates. The tool is designed around privacy and local operation—it runs on your Mac with no mandatory cloud dependency, and can use local language models through Ollama or LM Studio instead of sending data to external APIs. It also integrates with cloud-based LLMs like Claude, ChatGPT, and Gemini if you prefer.
The project shows consistent development with regular commits addressing bugs, feature refinements, and user-reported issues. Pull requests are reviewed and merged steadily, indicating active maintenance. The codebase receives ongoing improvements to core functionality like timeline accuracy and chat reliability. Documentation is maintained alongside feature additions, and the project responds to user feedback with targeted fixes rather than major rewrites.
