Health, home and travel decision
PokeItem
A technical user can build a limited self-hosted replacement (scan, store, aggregate prices) but reproducing PokéItem's continuous cross-market index accuracy, polished mobile recognition, and integrated market access is non-trivial without the vendor's proprietary data and refinements.
Visit website↗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
$120/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 scans or selects cards → app identifies card + variant → app fetches market prices → store/aggregate card in user's collection → display portfolio value and stats
What it still won’t have
- The vendor's continual cross-market price index and its historical calibration
- Polished mobile camera UX and high-accuracy card recognition tuned to Pokémon TCG variants
- Built-in marketplace integrations and any negotiated access to CardMarket data
- Existing user base, ratings, and platform trust/brand
What remains hard
- Proprietary data
PokéItem connecte chaque carte de votre collection aux prix réels des marchés français, anglais, italien, allemand, espagnol et japonais, croisés en continu depuis CardMarket, eBay et l'indice de prix PokéItem.
First-year cost
No published price
PokeItem 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
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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 Pokémon TCG collection manager as a web-first PWA using React (frontend), Node.js + Express (API), PostgreSQL (storage), and a small Python microservice for image recognition. Core features in scope: (1) mobile camera capture and upload UI that sends images to the Python service; (2) card identification endpoint using a pre-trained vision model (use TensorFlow or a hosted vision API), returning card id, language, variant and rarity; (3) price aggregator that calls eBay and CardMarket public search pages/APIs (or scrapes if no API) and computes a consolidated euro price index; (4) REST CRUD for user collections and bulk-add by selecting a set; (5) scheduled job (cron) to refresh prices and compute portfolio value + P&L; (6) simple auth (email), export CSV, and basic tests for API endpoints and recognition pipeline. Out of scope: training a bespoke vision model from scratch, marketplace buy/sell flows, payments/subscriptions, and advanced fraud/anti-scraping infrastructure. Include error handling for network and parsing failures, retry/backoff on external requests, rate-limit protections, end-to-end tests for core flows, and Docker deployment manifests for hosting on a single VPS.
How we checked
How the score was reached
- Partly verdict base52
- 3/3 assessment runs agreed+4
- Hard moats found in the evidence-3
- Evidence score53
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 →Integrity checks
What held up, and what did not.
