This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
ScreenMind captures your screen, understands it with a single local Gemma 4 model, and turns it into a searchable, chat-able memory. Now it also transcribes meetings right in your browser (Google Meet, Teams, Zoom), lets you pick your model and quantization from the dashboard, and runs natively on macOS. 100% local, private, open-source — the alternative to Microsoft Recall.
Hey Product Hunt 👋 Ayush here, I build ScreenMind.
Why I built it: I kept losing things I’d seen: a message on Discord, a link in some tab, an error I’d fixed a week earlier. Microsoft’s Recall had the right idea, but it stored everything in plaintext and needed a Copilot+ PC. I wanted the same kind of memory where nothing ever leaves my laptop, running on the GPU I actually own: a 4GB GTX 1650.
What it does: it captures your screen when it changes. A single local Gemma 4 model reads each screenshot and works out what you were doing; it also handles your voice notes and meetings. You can then search or chat with your history (“what did Alex say about the deploy?”). It’s all on your machine and MIT licensed.
What changed since the last launch: most of the work went into using it daily and fixing what broke.
Meeting transcription only recognised desktop apps, so my own Google Meet calls in Edge were never picked up. It now detects Meet, Teams and Zoom in browser tabs too. The first version also caught YouTube videos about Teams, so it’s now much stricter about what counts as a meeting.
There’s now a Model Hub: pick the model and quantization that fit your GPU, download it and switch, all from the dashboard. No terminal needed.
Incognito now truly records nothing, meetings included.
Native macOS window detection. That’s the project’s first outside contribution, and it made my week.
How my approach changed: early on I kept adding features. This time I mostly read the code back, wrote tests, and fixed the quiet bugs that only show up after weeks of real use. It’s slower, but it’s what makes something you leave running all day trustworthy.
I’d love feedback, especially from people on macOS/Linux or on low-VRAM GPUs, since those are the setups I can test least myself. What would you want a screen memory to remember for you?
ScreenMind was also featured on GitHub’s Open Source Friday, if you’d like a full walkthrough: https://www.youtube.com/watch?v=N_cGKFGMxxc
pip install screenmind · github.com/ayushh0110/ScreenMind
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About ScreenMind on Product Hunt
“Remember everything, Share nothing”
ScreenMind was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #122 on the daily leaderboard. ScreenMind captures your screen, understands it with a single local Gemma 4 model, and turns it into a searchable, chat-able memory. Now it also transcribes meetings right in your browser (Google Meet, Teams, Zoom), lets you pick your model and quantization from the dashboard, and runs natively on macOS. 100% local, private, open-source — the alternative to Microsoft Recall.
ScreenMind was featured in Productivity (663.7k followers), Open Source (69k followers), Artificial Intelligence (481.7k followers), GitHub (41.4k followers) and YouTube (17k followers) on Product Hunt. Together, these topics include over 356.5k products, making this a competitive space to launch in.
Who hunted ScreenMind?
ScreenMind was hunted by Ayush. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how ScreenMind stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Ayush