Search that understands what you meant
Full-text search with autocomplete across everything you’ve saved — plus semantic search that finds notes by meaning, even when the words don’t match.
Everything you put into Dexi — notes, bookmarks, emailed articles, feed entries — lands in one searchable index. Titles, body text and tags are all covered, with autocomplete that suggests matches as you type.
On top of that sits semantic search. Every note gets a meaning-based fingerprint, so you can search for the idea rather than the exact phrase. “That article about founder burnout” will surface a piece titled “Why startup CEOs quit” — no shared keywords required. Every note also has a “similar notes” view that surfaces its nearest neighbors by meaning.
Why it matters
A capture system is only as good as its recall. The real failure mode of note-taking isn’t losing notes — it’s writing them and never finding them again, because eight months later you don’t remember the words you used. Semantic search removes that dependency: you search with today’s vocabulary and still find last year’s thinking.
Because search spans every content type, you stop caring where something came from. Whether an idea arrived as a note you typed, a page you bookmarked, a newsletter you forwarded or an RSS article that flowed in — it’s one query away.
Who gets the most out of it
- Anyone with more than a hundred notes — Keyword search degrades as an archive grows; meaning-based search gets more valuable with every note you add.
- Lawyers and compliance teams — Find every note touching a concept — not just the ones that use this year’s terminology for it.
- Content creators and writers — “Have I written about this before?” gets a real answer, plus the similar-notes view hands you related material for the piece you’re drafting.
- Engineers and technical writers — Search architecture decisions and incident notes by concept when you can’t remember which system they were filed under.
Example: A writer hunting a half-remembered idea
You’re drafting an essay and recall reading something months ago about how cities get more productive as they grow while companies get less so. You have no idea what it was called or where you saved it.
- You type “why cities scale better than companies” into search.
- Semantic search returns a bookmarked article titled “Geoffrey West on superlinear scaling” — saved five months ago from a newsletter, with none of your query words in the title.
- From that note, you open Similar notes and find two more: your own reading note on “Scale” and a feed article about organizational overhead.
- Three sources for your essay, recovered in under a minute, from a search phrased entirely in your own words.
Try it in your own workspace — free, no credit card required.
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