BrainLoom
Turn PDFs into Flashcards. The local-first Learning OS.
404 followers
Turn PDFs into Flashcards. The local-first Learning OS.
404 followers
Stop switching between different apps just to study. BrainLoom is the local-first Learning OS that unifies your study workflow. Turn PDF highlights into Flashcards instantly and keep them linked to the source text for deep context. You can also structure ideas visually on an Infinite Canvas using "Smart Paste" without touching your mouse. Available for Windows v1.0 (Mac soon). To fund the expansion, grab a Lifetime License for $29 today (First 150 users only).
BrainLoom
@jakub_ner Great question. BrainLoom stores everything locally (ISER), so you always own your data. Today, you can right-click to import notes (.md, .txt) directly into the app, which makes getting started straightforward.
In v1.0.2, which is coming in the next 1–2 weeks, I’m adding mass import support, including drag-and-drop for multiple files, to make migration much smoother.
The "View Source" feature is genuinely killer - I've always hated losing context when reviewing flashcards weeks later. The fact that you built FSRS v6 directly into the app (not as a plugin) shows serious commitment to the learning science. As a fellow knowledge worker drowning in PDFs, the Smart Paste for mind maps without touching the mouse sounds like a huge time-saver. Is the Mac version planned for Q1 2026, or later in the year?
BrainLoom
@easytoolsdev You hit on the exact three pillars I obsessed over! Integrating FSRS natively was non-negotiable for me—plugins are too fragile for something as critical as memory.
On the Mac Version: Definitely Q1. Actually, Since the code is already written (Flutter), I am aiming to have a Beta in the hands of users by mid-February. If you grab a license now, you lock in the Founder's price and get that Mac build the moment it compiles!
Turning PDF highlights into linked flashcards is powerful. How do students usually review or resurface those cards over time inside BrainLoom?
BrainLoom
@noha_elmeselhy Great question, Noha!
I integrated the FSRS Algorithm directly into the app.
When you create a card, I automatically schedule it into a daily queue based on how well you remember it. You just open the app, click the 'Review' tab, and app serve up the exact cards you're about to forget. No manual scheduling needed!
@ujjwalranga That makes sense — integrating FSRS directly removes a lot of friction.
I like the “review what you’re about to forget” approach, it feels very user-centric.
Nice implementation 👍
BrainLoom
@drskram Hi! First, thank you for the kind words on the UI, and even more for this brutal, honest feedback. This is exactly what I need to make the app better.
Here is the breakdown:
1. The Crashes (2k+ Pages & Outlines):
This is a memory optimization issue with the current PDF renderer. I am moving this to Critical Priority. I will push a hotfix for large-file handling and PDF Outlines (Table of Contents) in the next update.
2. Image Support (Notes & MCQs):
You are right—visual learners need Image Occlusion and image-based cards. This is currently planned for Q2. I focused on text first to get the Flash-Loom engine perfect, but images are next.
3. Exports:
Right now, you can export decks to Anki/CSV, but full annotation export is still in development.
My Offer to You:
If you are willing, please join the Discord (link in bio) and DM me. If you can share the specific PDF that caused the crash (or a similar size one), I will use it to debug the engine and ping you personally when the fix is live.
I want to earn your premium purchase, not just ask for it.
Local-first is refreshing, but how do you see syncing or backups fitting in log term without compromising that philosophy?
BrainLoom
@ill_robyn Great question. v1.0 is strictly local (folder-based) for privacy. For v2.0, I plan to offer optional encrypted cloud sync, but the local-only mode will always exist for those who prefer full sovereignty over their data
Very useful product with good UI/UX. Can I know which stack did you use?
BrainLoom
@szymcode Thanks! I poured a lot of love into the design, so I appreciate that.
The stack is Flutter & Dart. For the database, I used Isar (it's blazing fast for local storage).
Agnes AI
Indeed I like BrainLoom's local first concept! Just curious - how often does it refresh the local memory?
BrainLoom