The right framing isn't ‘replace Anki’. It's ‘split the deck’.

No, and the honest 'alternative' pages for this topic should say so up front. AnKing, Zanki, and Pepper are roughly fifteen years of accumulated community work on the Step 1 and Step 2 blueprints, with thousands of student-iterated tags and dozens of maintainers. No AI can replicate that catalogue inside a year, and any tool that pretends to has not used AnKing seriously. What Anki is bad at is what you are actually annoyed about: class exams on your professor's slides, where no community deck exists and manual carding a 90-slide lecture takes you an hour of typing. The two problems are different and the right move is to split them, not pick one tool.

Two decks living in the same Anki collection. Boards deck (AnKing or Zanki or Pepper, untouched, synced via AnkiHub if you use it) for Step content. Class deck (Studyly-generated, imported as .apkg per lecture) for everything your professor put on slides for the Tuesday exam. The Studyly .apkg uses Studyly-namespaced note types so an import lands as a new top-level deck without overwriting any AnKing card, tag, or note type. You can drag it under a class folder, suspend selectively, or delete the whole thing if a professor's emphasis changes, and nothing in AnKing moves.

ChatGPT will write you a list of questions. It does not enforce a quality rubric, pin questions to the specific slide they came from, track per-question retention, reword stems on revisit, generate image-occlusion masks over labeled diagrams, or carry source anchors into a .apkg. Studyly does all six. On a held-out three-document eval (a microbiology lecture, an internal medicine deck, a pharmacology PDF), generated MCQs were scored blind on factual correctness, clarity, distractor quality, and question-type coverage. Studyly scored 81.3 of 100. The next best generator on the same documents scored 78.0. Turbolearn scored 57.8. The pre-output rubric gate is what closes the gap.

Studyly extracts the figure, identifies the labeled structures, and writes an image-occlusion card with a mask over each label. Those cards go into the .apkg as image-occlusion notes, with the underlying image embedded, so when you import into Anki the cards work the same way a hand-built image-occlusion card does. A 90-slide anatomy lecture with twelve labeled diagrams produces roughly 200 MCQs plus 12 image-occlusion cards in one package.

No. The .apkg ships with a Studyly-namespaced note type set ('Studyly MCQ', 'Studyly Cloze', 'Studyly Image Occlusion'), so they sit alongside the AnKing note types without overwriting. Filtered decks built from AnKing tags do not see Studyly cards unless you explicitly include the Studyly note type. If you decide later that you want them gone, deleting the imported deck removes the cards and you can clean up the note types in one step.

Yes for the class-exam side. The boards-content half of the split changes by program (UWorld for NCLEX, Boards Vitals for INBDE, RxPrep for NAPLEX, etc., not all of those have a community Anki deck the size of AnKing), but the generator is content-agnostic on the input side. PowerPoint, Keynote, PDF lecture handouts, scanned textbook chapters, and YouTube lecture videos are all in scope. The .apkg export is the same.

Free tier, no card. Signup is email and password on app.jungleai.com. There is no 3-day-trial that becomes a charge. You can drop a lecture, generate cards, export the .apkg, and import into Anki without entering a credit card anywhere in the flow. Paid is opt-in and removes a per-account deck cap.

Use them. Schools where an upperclassman cohort maintains a class-specific community deck have already solved the problem this page is about, and you would be silly to ignore that work. The realistic case where Studyly helps is the much larger one: schools with no class-deck culture, professors who change their decks year over year so any past-cohort cards are stale, electives, and rotations where you are getting handed a brand new PDF every week. For those, generating from the actual deck is faster than waiting for a maintained class deck that will not exist.

Because the documents were not used to train any of the four generators, the rubric (factual correctness, clarity, distractor quality, question-type coverage) was applied identically to every output, and the scoring was blind. The point of holding out the documents is that the generators cannot have memorized them, so the score reflects how the generator handles a slide deck it has not seen before, which is exactly the medical-school use case. The eval lives in Jungle's internal admin Quality Comparison panel, dated 2026-04-24.

Two. First, the lack of a boards-content moat means students who switch wholesale lose access to AnKing's tag tree, AnkiHub sync, and fifteen years of community polish, and then have to rebuild a fraction of that on the new tool, which never happens. Second, most replacement pitches do not enforce a real rubric on the question side, so the cards generated for class content are weak, distractors do not discriminate, and the same stem reappears unchanged on revisit so pattern-matching kicks in by the third pass. The two-deck split sidesteps both. Anki keeps its moat; Studyly keeps its rubric and reword-on-revisit; the .apkg is the bridge.