ReMind
Local-first AI memory that captures your digital activity privately on-device.
ReMind is a promising open-source experiment for local AI memory, currently macOS-only and early-stage. Its privacy-first approach and active community are commendable, but it lacks polish and cross-platform support. Worth trying if you value data sovereignty and don't mind tinkering.
- Privacy-focused knowledge workers who want a local memory assistant
- Developers seeking an open-source, customizable memory tool
- Researchers tracking digital activity across apps
- Users wanting an offline alternative to Microsoft Recall
- Users needing cross-platform support (currently macOS only)
- Those wanting a polished, production-ready app
- Users who require cloud sync or collaboration features
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In short
ReMind — Local-first AI memory that captures your digital activity privately on-device. Best for Privacy-focused knowledge workers who want a local memory assistant, Developers seeking an open-source, customizable memory tool, Researchers tracking digital activity across apps. Free to use.
Viability Score
How likely is ReMind to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- On-device AI processing (no cloud)
- Screenshot and app usage capture
- Natural language query interface
- Local indexing of digital activity
- Privacy-first design (data never leaves device)
- Open-source codebase (Swift)
- Roadmap for phi-3-vision integration
- Configurable capture prompts (planned)
- Community-driven development
- Offline operation
- macOS-only (Mac Catalyst hinted for future)
- Discord community support
- GitHub repository for contributions
- Active development with updates
About ReMind
ReMind is a free, open-source macOS app that records your digital activity and makes it searchable via natural language queries, all processed on-device. Designed for privacy-conscious users, it uses Apple's Core ML and local LLMs to index screenshots, app usage, and text snippets without sending data to the cloud. The app is built with Swift and emphasizes user control, offering an offline alternative to services like Microsoft Recall. Currently in early development, ReMind targets knowledge workers, researchers, and developers who want a personal AI memory that remembers context across apps. Its roadmap includes integrating on-device vision models like phi-3-vision and configurable capture prompts. The project is community-driven with an active Discord and GitHub repository, inviting contributions. While macOS-only today, the developer has hinted at future iOS support. ReMind differentiates itself by being fully open-source and privacy-first, contrasting with cloud-dependent memory tools. However, users should expect beta-level stability and a hands-on setup experience.
Behind the Verdict
ReMind enters a space dominated by Microsoft's Recall, which faced privacy backlash. Its key advantage: everything runs locally, no data leaves your machine. This makes it attractive for security-conscious users who want a personal search engine for their digital life. The active community on Discord and GitHub suggests momentum, with users praising its potential despite being a 'beginner project'. However, it's far from production-ready. Currently macOS-only, with no ETA for Windows or Linux. The app captures screenshots and app usage, but indexing can be slow and queries sometimes miss context. Setup requires some technical comfort—compiling from source or following setup guides. Integration with phi-3-vision is planned but not yet implemented. Compared to commercial tools like Rewind (now Mem), ReMind lacks polish, cloud backup, and team features. But for a single user who wants total privacy and is willing to contribute to development, it's a compelling option. We'd reach for it when experimenting with local AI memory, not for daily mission-critical recall.
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Use Cases
- Search for where you saved a file or note from yesterday's meeting
- Retrieve a forgotten URL or document title from a previous browsing session
- Ask 'What did I work on last Tuesday?' and get a summary of captured activity
- Use on-device memory to help with daily standup notes
- Index your app usage for personal productivity analysis
Models Under the Hood
Limitations
- ReMind is in early development; the app may have bugs and limited features.
- It currently only runs on macOS (no Windows/Linux/mobile).
- The AI model capabilities are basic, and advanced features like video screen capture or structured memory are not yet implemented.
- Users must build from source or install via side-loading; no App Store distribution yet.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
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