A reading companion for lifelong learners

Read once.
Remember forever.

MemoryLynx is a study partner for the things you read, watch, and listen to. It distills each source down to a few ideas worth keeping — with the original passage cited beside each one — then quietly brings them back, just before you’d forget.

Free · 10 captures, no cardPro USD $8/mo · or $72/yr
3–5high-level insights pulled from each source — not hundreds of trivia cards.
everyclaim is cited back to its original passage. If we can't cite it, we flag it.
a fewminutes a day. Reviews are paced by FSRS — just before forgetting, never sooner.
How it works

Three steps between
reading and remembering.

Most reading tools collect highlights. The highlights then sit in a folder, and the books quietly fade. MemoryLynx closes the loop — capture, distil, return — so the things you cared enough to read actually stay with you.

i.

Capture it

Drop a link, a PDF, a podcast, a photo of your handwritten notes. Forward a newsletter. Eight ways in — whatever your reading life looks like.

URLPDFAUDIONOTE
ii.

Distil with citations

Claude pulls out the few ideas actually worth remembering — and pins each one to the passage that said it. Page numbers, timestamps, line offsets, all preserved.

iii.

Remember, gently

FSRS schedules each idea to come back just before you'd forget. Five formats — comprehension, cloze, multiple choice, Q&A, teach-it-back — chosen to fit each idea.

COMPCLOZEMCQQ&ATEACH
Capture

Bring in whatever you’re reading.

Capture friction is what kills most learning tools. So we made eight ways in — one for nearly every shape your reading life takes.

i.

Web articles

Paste any link — The Atlantic, a Substack, a Wikipedia rabbit-hole. Article body extracted; the full text is kept so we can cite back to it.

ii.

YouTube lectures

Drop the URL. We pull the transcript with timestamps; the citation on each insight is a click that jumps you to that very second.

iii.

PDFs & ebooks

Research papers, book chapters, course readings, up to 50 MB. Page numbers preserved, so citations point at the page you can flip back to.

iv.

Podcasts & lectures

Drop in an MP3 or a recording from class. We transcribe it sentence-by-sentence; citations are clickable and play right back.

v.

Photos & whiteboards

Snap a textbook page, a meeting whiteboard, a page of your own handwritten notes. Vision reads it like a careful student would.

vi.

Forwarded newsletters

You get a private inbox. Forward Stratechery, the Browser, your favourite Substack — it lands in your knowledge base by morning.

vii.

Notes & thoughts

Paste a meeting transcript, a long voice note, a journal entry, a conversation. The same gentle distillation runs over it.

viii.

Readwise & Kindle

Bring your highlight history with you in one import. Hit the ground running with a populated library on day one.

Soon

Browser extension

One-click capture from any page, with selection highlighting. Coming next.

No invented facts

Every idea, cited.
Every claim, traceable.

AI summary tools have one shared failure mode: they make things up. We built MemoryLynx so they can’t. Each insight remembers the exact passage that produced it — character offsets in text, timestamps in audio, page numbers in PDFs. If we can’t ground a claim, we mark it for your review rather than pass it off as fact.

The source · Cal Newport, Deep Work, ch. 2

4,212 chars23 paragraphspage 18 of 287

The shift from open-plan office to social media to constant chat has, paradoxically, eroded our capacity to do the very thing knowledge work asks of us.

Attention residue is the cost paid for context-switching: when you turn from one task to another, a portion of your attention remains stuck on the prior task. The cost compounds across the day.

Sophie Leroy’s 2009 study at Minnesota measured this directly. Subjects rotated between brand-evaluation tasks under two conditions — finished, or interrupted.

In the interrupted condition, performance on the second task dropped 17–24% even when participants reported feeling fully focused. The brain doesn’t care what you think you’re paying attention to.

What MemoryLynx remembers · 2 of 4 grounded

i.
Context-switching is never free — every transition leaves a residue of attention on the prior task that degrades performance on the next.
Attention residue is the cost paid for context-switching…¶ 7 · pg 18
Core argumentyour focus: what I want to remember
ii.
Even when subjective focus felt complete, recently-interrupted subjects performed 17–24% worse on the second task — felt focus is a poor metric.
Performance on the second task dropped 17–24%…¶ 9 · pg 18
Facts & datareview format: cloze deletion
A daily review

Five ways to practise.
The right one, automatically.

A definition isn’t an argument. A formula isn’t a framework. Different ideas call for different kinds of practice — and your review session interleaves them, so you’re never just on autopilot.

Free text · graded gently
In your own words: why does massed practicefeel more effective than spaced practice — and why is that intuition systematically wrong?
During massed practice the material is in working memory, so we’re recognising rather than retrieving. It feels like learning — but at a week’s remove, spaced practice is around 2.4× stronger because retrieval becomes effortful. Bjork called it desirable difficulty
⌘ ↵ submit⌘ S skip
Ask your library

The reading you forgot you did, made askable.

Three months from now, you’ll have eighty articles, a dozen papers, forty hours of podcasts in here. Asking your library is how you actually find any of it again.

Q.What have I read about attention residue?retrieved 5 of 142 · in 3.2s
A.
Attention residue is the cognitive cost of context-switching: a portion of your attention remains stuck on the previous task[1]. The empirical anchor you’ve saved is Sophie Leroy’s 2009 study, which measured a 17–24% performance drop on subsequent tasks even when subjects reported full focus[2]. You also marked Newport’s argument that this compounds across the day under modern office conditions[3], and a counter-take from a Cognitive Psychology paper noting that brief task-related daydreaming may dampen residue rather than amplify it[4].
[1]
Newport · Deep WorkPDF · pg 18
[2]
Leroy 2009 · OBHDPPDF · pg 4
[3]
HBR · The Open OfficeURL · ¶ 14
[4]
Stanford podcastaudio · 23:14
A different kind of tool

Not flashcards.
Understanding that lasts.

The category looks busy — eighteen flashcard apps, all making the same flashcards. MemoryLynx is built for a different person, asking a different question.

Feature
Flashcard apps
MemoryLynx
Built for
Students cramming for exams
Lifelong learners & professionals
Atomic unit
Hundreds of low-level facts per deck
3–5 high-level insights per source
Source citations
— optional, often missing
First-class · page · timestamp · offset
Default review
Recognition (Q&A)
Comprehension (free text, AI-graded)
Cross-source synthesis
— deck is the unit
Ask your whole library
Pricing · in US dollars

Less than one new
paperback a month.

The free tier is generous enough to actually use. Pro removes the limits. No hidden seats, no enterprise calls.

Free
USD0 /forever

For trying the loop on a few sources.

  • 10 captures / month
  • 5 AI extractions / month
  • 5 review prompts / day
  • 30 minutes audio / month
  • 10 library queries / month
  • 50 knowledge items total
  • One-time Readwise / Kindle import
RECOMMENDED
Pro
USD8 /month

Or USD $72 a year (≈ $6/mo). Cancel anytime.

  • Unlimitedcaptures, extractions & library
  • 15 review prompts / day · longer sessions
  • 20 hours audio / month · podcasts welcome
  • Unlimited library queries
  • Unlimited Teach-it-back evaluations
  • Anki, Notion, Obsidian & CSV export
  • Shareable insight cards & weekly digest
Honest answers

Questions, mostly answered.

How is this different from Anki, Readwise, or AnkiDecks?+

Anki is a flashcard runtime — you write the cards. Readwise stores your highlights and surfaces them. AnkiDecks generates flashcards from sources. MemoryLynx pulls a small number of high-level insightsper source, grounds each one to the exact passage that produced it, and reviews them with comprehension prompts — not recognition flashcards. Different unit, different practice, different outcome.

Won't the AI just hallucinate insights?+

It’s the failure mode we built against. Every extraction stores the offset of the source span that produced it — character offsets in text, timestamps in audio, page numbers in PDFs. If the system can’t ground a claim, it’s flagged as “synthesised — review carefully” rather than passed off as fact. We track the ungrounded rate as a quality metric and target under 10%.

What's the algorithm? SM-2? FSRS?+

FSRS-5. It’s the modern, ML-trained successor to SM-2 — better long-term interval estimates, more responsive to lapses. We use the same rating mapping (Again / Hard / Good / Easy) across all five review formats.

Can I get my data out?+

Yes. Pro includes export to Anki (.apkg), Notion, Obsidian and CSV. Free accounts can read everything via the API and self-export. We don’t lock anyone in — the goal is for the loop to be good enough that you don’t want to leave.

Is my reading data used to train models?+

No. We send your text to Anthropic’s Claude API for extraction and grading, with the no-training opt-out enabled. Your library stays your library — never shared, never used for fine-tuning.

Mobile app?+

The web app is a PWA — installable to your home screen, with offline review and notifications. Native iOS and Android are post-launch on the roadmap, prioritised by user feedback.

The reading you do this year
doesn’t have to vanish.

Capture three things you read this week. Look for them next month. See if they stuck. The loop only takes minutes a day.