Ask a UX researcher where last quarter’s desk research lives and you’ll usually get a sigh: some links in a doc, some in browser bookmarks, key findings buried in PDFs nobody reopens. Marqly gives you a repository for secondary research that maintains itself — every study and article you save gets tagged by AI automatically, your highlights mark the findings inside them, and semantic search retrieves any of it by describing what it said.
Highlight the finding, not just the link
A bookmark records that a study exists. Your job is the finding on paragraph fourteen. Marqly’s highlighter lets you select text on any website and mark it in six colors — enough to run a real coding scheme, like one color for statistics, one for quotes, one for methodology notes, one for claims you want to verify. Attach a note to any highlight to record your interpretation while it’s fresh.
Two properties make this repository-grade rather than a browser gimmick. Highlights persist on the page, so revisiting a source shows your markup exactly where you left it. And they sync to your library, so all key findings across every source sit in one searchable place — you can review the evidence without reopening a single original tab. The full workflow is covered in how to highlight text on any website.
Retrieval by meaning, because that’s how memory works
Researchers don’t recall sources by title; you recall “the diary study where participants abandoned the task at the confirmation step.” Keyword search fails that query. Marqly’s semantic search matches by meaning across titles, page content, your highlights, and video transcripts, so describing the finding is enough to surface the source. If your search habits were shaped by folder-and-keyword tools, searching bookmarks with AI shows what changes.
AI summaries help at the other end of the pipeline. When a literature scan leaves you with twenty tabs of maybe-relevant papers and articles, the auto-generated summary on each save lets you triage the pile quickly and decide what deserves a close read. The tab saver captures the whole scan session in one action first, so nothing gets lost when the browser inevitably restarts.
Talks and conference sessions count as sources too. On any YouTube watch page, Marqly shows an AI card with a streaming summary, key sections, and a playback-synced transcript; bookmarking the video attaches that transcript to the save. A 45-minute methods talk becomes text your search can reach into.
Reading rarely stays at your desk, so the repository shouldn’t either. Saves and highlights sync between the extension, the web app, and the iOS app, and the extension’s side panel lets you search your library next to whatever page you’re currently reading — useful when you’re checking whether a new article contradicts a study you saved in March, without losing your place in either.
Share findings without an access request
Research that nobody sees changes nothing. Marqly boards group related links and highlights — one per project, per study area, or per recurring stakeholder question — and any board can be shared as a public page that viewers open in a browser with no signup and no license seat. That removes the classic repository failure mode where insights die behind a login the design team never requests.
The honest constraint: sharing is one-directional and public. Teammates can read your curated board but can’t contribute to it, and anyone with the link can view it, so participant-identifying material stays in your properly access-controlled tools, not on a shared board.
Getting started
Set up takes three steps. Install the extension in Chrome, Edge, Firefox, or Safari. Import what you already have — Marqly accepts standard browser bookmark HTML exports, plus Pocket exports and Raindrop.io collections, so an existing pile of research links comes along instead of starting from zero. Then let the AI tag the lot; the backlog that would have taken a weekend to organize into folders becomes a tagged repository without manual filing. From then on, the routine is just: read, highlight, move on. If you want a manual layer anyway, project codes or method names take seconds to add as tags at save time and ride on top of what the AI applies. The whole loop works on the free tier, and the extension holds a 4.8 rating on the Chrome Web Store if you want a second opinion before installing.
Start free at app.marqly.com — no card required.
Who this isn’t for
If your team needs a governed research repository — raw interview recordings, participant consent tracking, shared taxonomies, per-project permissions, multi-researcher collaboration — Marqly isn’t that, and pretending otherwise would waste your evaluation time. It has no team or collaboration features beyond view-only public boards, and no API for pushing data into other systems. Where it earns its place is the layer most repositories neglect: the continuous stream of published studies, articles, and talks a working researcher reads, marked up and retrievable in seconds.
Frequently asked questions
Is Marqly a full research repository like enterprise tools?
It's the lightweight version. Marqly stores secondary research — published studies, articles, competitor teardowns, talks — with AI tagging, highlights, and semantic search. It doesn't handle raw session recordings, participant management, or team-wide taxonomies the way dedicated enterprise repositories do. For a solo researcher or a small team that mostly needs published sources organized and retrievable, that trade is usually worth it.
Can my teammates see my research boards?
Yes, through public sharing. Any board can be published as a public web page, and anyone with the link can view it without creating an account — useful for circulating a literature review or a findings digest. It's view-only: teammates can't edit or add to your board. And because the page is public to anyone holding the link, keep confidential participant data out of shared boards.
Do my highlights stay on the original article?
They do. When you highlight text on a page, the highlight is saved to your Marqly library and also persists on the page itself — reopen the study next month and your color-coded markings are still sitting on the exact passages. That means rereading a source is a review of your past analysis, not a fresh start from paragraph one.