Learning and careers decision
Vocaland
A capable developer can realistically build the core OCR + spaced-repetition + deck-sharing workflow, but reproducing Vocaland's native iPhone polish, large curated lexicon, and social leagues at the same level would be effort-intensive—so build a narrow replacement but keep paying for the full product experience.
Visit website↗Built by Dmytro Katyukha, who ships 3 products in this index
Not priced
No pricing page we fetched carried a figure, so there is nothing to compare against. The build side is still real.
$100one-off120 h to build
$30/mo6 h/mo upkeep
No published price to break even against.
No open-source build does this yet
Nothing published replaces this one, so a replacement starts from an empty file. Here is what it would have to cover.
What a replacement has to do
- User captures words (photo/screenshot or manual), app extracts text and suggests translations, words are turned into short review sessions using a spaced-repetition schedule, user reviews cards and progresses; optional sharing of decks and basic stats.
What it still won’t have
- Native iPhone polish and App Store distribution
- Built-in curated 4,000+ word lexicon across 11 languages
- Refined mobile UX (10-minute sessions tuned for native performance)
- Social leagues, achievements, and polished friend-competition experience
- Cross-device sync and any proprietary backend optimizations
What remains hard
- Product polish and ongoing maintenance
First-year cost
No published price
Vocaland does not publish a price we could read, so there is nothing to compare against. What building costs is below.
Money you would actually spend
Time you would spend
—
What you would spend
What we assumed
The verdict above measures whether you could build it. This one is only about money.
Runnable build prompt
Build a minimal, self-hostable web vocabulary app using React for frontend, Node.js/Express for API, Postgres for storage, and Tesseract.js (or a cloud OCR fallback) for image-to-text. Core features in scope: user signup/login, upload photo/screenshot and OCR text extraction, translate/suggest target words via an external dictionary/translation API, create/save cards to decks, an SM-2 spaced-repetition scheduler for review sessions, simple 10-minute session UI with card answering flow, deck sharing via exportable JSON link, and basic progress stats (daily/weekly). Out of scope: full native iOS App Store build, providing a curated 4,000-word multilingual lexicon, advanced gamification/leagues, and offline-first mobile polish. Include input validation, error handling for OCR/translation failures, unit and integration tests for the scheduler and API endpoints, and deployment scripts (Dockerfile + docker-compose) with a README for setup.
How we checked
How the score was reached
- Partly verdict base52
- 2 cited sources+1
- 3/3 assessment runs agreed+4
- Evidence score57
The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.
How scoring works →Cited sources · 2
Every page the run actually retrieved.
Integrity checks
What held up, and what did not.
