ReMyndhow to find something you saw on your screen
you saw it. you are sure of it. a number, a name, a link, a line in someone's slide. you closed the tab and moved on, and now you need it back and it is nowhere.
the single biggest thing people use ai for is searching for information. per the anthropic economic index, "search electronic sources, databases, or repositories for information" is the number one work task in ai conversations globally, at around 5% of all usage. but every one of those tools searches the open web or a corpus someone else assembled. none of them can search what you already looked at.
here is every real method, roughly in order of how much effort it costs you, and where each one runs out.
start with browser history, properly
most people search browser history wrong. they hit cmd+y, type a word, find nothing, and give up.
two things to know. first, chrome and safari search page titles and urls, not page content. if the thing you remember was in the body text, the title probably does not contain it. search for something that would plausibly be in the title instead: the site name, the product, the section.
second, use the date. if you can place it within a day or two, scrolling the history for that afternoon is often faster than guessing keywords. you recognise a page when you see it far more reliably than you can describe it.
where it runs out: roughly 90 days of retention by default. only pages loaded in that browser. nothing from a desktop app, a pdf, a screen share, or a message.
spotlight, and what it actually covers
spotlight indexes file contents, not just names, so a phrase inside a document or a pdf is genuinely findable. and modern macos runs live text over images, which means text inside a screenshot you saved can surface too.
that last part is better than most people realise and worth testing before you go further.
where it runs out: it only knows about files. the thing you are looking for has to have been saved as one. the overwhelming majority of what you look at in a day never becomes a file.
the screenshot folder you forgot about
if you are the kind of person who screenshots things reflexively, your screenshots folder is an accidental archive. sort by date, jump to the week in question, and scan. combined with live text, it is searchable.
where it runs out: it only contains what you thought to capture at the time. which is the whole problem. the things you need later are the things that did not feel important enough to screenshot.
ask the person
genuinely underrated. if the thing came from a conversation, a slack message or a call, asking "what was that link you sent me" costs thirty seconds and works.
where it runs out: it does not scale, it depends on someone else's memory being better than yours, and it is unavailable for anything you found on your own.
why these all fail in the same way
look at the pattern. every method above searches something you deliberately kept: a page you loaded in a specific browser, a file you saved, a screenshot you took, a message someone else sent.
but the thing you are trying to find is almost always in the other category. the number that was on screen for eleven seconds during a call. the apartment listing you closed. the config value in a doc someone shared. the api response you glanced at in a terminal.
you did not save any of it, because at the time it did not feel like it mattered. that is not a discipline failure. nobody can predict which detail they will need three weeks later, and a system that requires you to try is a system that will fail.
the category that solves it
screen memory tools invert the model. instead of asking you to decide what to keep, they record continuously and make everything searchable after the fact.
the mechanism is straightforward. the app captures your screen as a stream of frames. ocr reads the text out of each one, so a picture of a slack message becomes findable by the words in it. that text goes into a local index. then you search it, or ask an ai that answers from it.
the thing that makes this work is that ocr step. it is why screen memory can find text that was never a file, never synced, never saved: text inside a video call, inside a screenshared deck, inside an app with no export.
what to check before you install one
a tool that records your whole working life deserves more scrutiny than most software.
where does the archive live. on your machine, or on a company's servers. there is a real difference and the default matters more than what is possible.
can you get it out. rewind ai, the app that made this category popular, stopped recording entirely in december 2025 after its company was acquired. anyone who could not export their archive did not own a memory. they owned a subscription.
which model sees it. some tools hardcode a cloud model. others let you point at something local so inference never leaves the machine either.
trained on, or sold. two separate promises. you want both in writing.
where remynd fits
remynd records your mac, runs ocr on device, keeps the archive local by default, and lets you hit ⌘K to search or ask across everything you have seen and said. you can point the ai at a local model through lm studio if you would rather nothing go out for inference. optional cloud backup is encrypted and exports to your own s3 bucket.
it is the version of this built for someone who read the section above and cared about the answers. if you are weighing it against the alternatives, the rewind ai alternatives page has the full field.
download remynd free for mac → free to download, runs locally, no card.