AI Frameworks · JerryZLiu

Dayflow

Dayflow is a macOS productivity tool that automatically records screen activity and converts it into a structured work journal using AI analysis. It runs locally and privately on your Mac, with optional integration to cloud AI providers like ChatGPT, Claude, or Gemini.

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Source: GitHub — github.com/JerryZLiu/Dayflow

6.6k

GitHub stars

372

Forks

Swift

Primary language

MIT

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	JerryZLiu/Dayflow
Owner	JerryZLiu
Primary language	Swift
License	MIT — OSI-approved
Stars	6.6k
Forks	372
Open issues	72
Latest release	v2.0.0 (2026-07-03)
Last updated	2026-07-03
Source	https://github.com/JerryZLiu/Dayflow

What Dayflow is

Swift-based macOS application that captures lightweight screen recordings, processes them through pluggable AI backends (local Ollama/LM Studio or cloud APIs), and maintains a local SQLite-style database of timeline events. Provides natural-language chat interface over accumulated activity data.

Quickstart

Get the Dayflow source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/JerryZLiu/Dayflow.git2cd Dayflow3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Self-employed and freelance work tracking

Automatically generate accurate timesheets, daily standup notes, and weekly client reports without manual time entry. Export Markdown timelines for billing or project reviews.

Engineering team context documentation

Developers can quickly reconstruct what they worked on, share context-aware summaries in PRs or standups, and identify focus patterns to improve productivity.

Personal productivity audit and habit analysis

Users gain visibility into where time actually goes (vs. perceived usage), spot distraction patterns, and iterate on workflows with weekly reviews grounded in real data.

Implementation considerations

Requires explicit macOS Screen & System Audio Recording permissions; users must grant and maintain access in System Preferences.
AI provider setup is user-selected: choose between local models (Ollama/LM Studio setup required), free Gemini API, or CLI-based ChatGPT/Claude. Each path has different latency and privacy tradeoffs.
Storage grows over time with screen recordings; configure automatic cleanup via storage limits to prevent disk exhaustion.
Screen recording may impact system performance on older Macs or under heavy workload; monitor CPU/memory during continuous capture.
Data lives in ~/Library/Application Support/Dayflow/ and is not automatically synced or backed up; user is responsible for retention and disaster recovery.

When to avoid it — and what to weigh

Regulatory data residency requirements — If using cloud AI backends (Gemini, ChatGPT, Claude), screen summaries are sent to external providers. On-premises or regulated environments may require local AI only, which depends on third-party tool availability.
Centralized team surveillance — Dayflow is single-device, local-first. Organizations needing centralized employee monitoring across many users should use purpose-built MDM or workforce analytics platforms.
Real-time compliance or audit logging — Dayflow is designed for personal reflection, not forensic audit trails or legal hold. It lacks immutable logging, chain-of-custody controls, or integration with SIEM systems.
Windows or Linux environments — macOS-only application (requires macOS 14+). No Windows or Linux support mentioned.

License & commercial use

MIT License: permissive, allows commercial use, modification, and distribution with attribution and inclusion of license text. No restrictions on proprietary applications built on top.

MIT License permits commercial use, including bundling or reselling. However, verify that your intended use (e.g., white-label SaaS, hardware appliance) aligns with MIT terms. If bundling cloud AI provider code or integrations, review those providers' separate ToS. No commercial support or warranty mentioned in source data.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Adequate
License clarity	Clear
Deployment complexity	Low
DEV.co fit	Good
Assessment confidence	High

Security considerations

Local-first design reduces exposure if using local AI backends. If using cloud AI, screen summaries are sent to third-party providers (Google, OpenAI, Anthropic, etc.); review their privacy policies and data retention terms. macOS permissions model gates access; app can only record screens when permission is granted. No mention of encryption at rest, secure deletion, or audit logging. Screen recordings are stored plaintext on disk; deletion via automatic cleanup or manual removal. No signature verification or code signing claims provided.

Alternatives to consider

RescueTime

Mature commercial time tracking with cloud analytics, integrations to 100+ tools, and team dashboards. Requires sending activity data to servers; less privacy-focused than Dayflow.

Toggl Track

Popular manual and automatic time tracking with team features, invoicing, and reporting. Cloud-based; requires user action to start timers. Simpler than Dayflow but less AI-driven context.

Hugging Face / Local LLM workflows

If you only need the AI/NLP layer, you can run local models (Ollama, LM Studio, vLLM) independently. Requires building your own screen capture and timeline UI.

Software development agency

Build on Dayflow with DEV.co software developers

Download Dayflow for Mac or review the source on GitHub. Choose your AI backend (local, Gemini, ChatGPT, or Claude) and start capturing your day.

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Dayflow FAQ

Does Dayflow upload my screen recordings to the cloud?

By default, no. Recordings and database stay on your Mac. If you choose a cloud AI provider (Gemini, ChatGPT, Claude), summaries of your activity are sent to that provider for analysis. You can use local models (Ollama/LM Studio) to keep everything offline.

Can I export my timeline data?

Yes. Dayflow supports Markdown export for any date range, useful for status updates, client notes, or archival. No mention of JSON, CSV, or other formats.

Is there a Windows version?

No. Dayflow is macOS-only (requires macOS 14+). No Windows or Linux support is available.

How much disk space does Dayflow use?

Depends on recording length and frequency. App provides automatic cleanup settings to limit storage; you can configure purge policies. Exact storage estimates not provided.

Work with a software development agency

DEV.co helps companies turn open-source tools like Dayflow into production software. Our software development services cover the full lifecycle — architecture, web development, integration, and maintenance — delivered by software developers and web developers who ship. Engage our software development agency to implement or customize it for your ai frameworks stack.

Ready to automate your work journal?

Download Dayflow for Mac or review the source on GitHub. Choose your AI backend (local, Gemini, ChatGPT, or Claude) and start capturing your day.

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