Beltstra
Photograph a binder page. Every pocket, priced.
Details
- External ID
- 1252728
- Source
- PH
- Company
- —
- Product
- Beltstra
- Website domain
- producthunt.com
- Launched
- Sept. 17, 2026
- Cohort
- —
- Upvotes
- 2
- Upvotes percentile
- 0.7405388069275176
- Tags
- Productivity, Artificial Intelligence, E-Commerce
- Fetched at
- Sept. 18, 2026, 4:40 a.m.
- Updated at
- Sept. 18, 2026, 4:40 a.m.
Description
Lay a page of your real card binder flat, take one photo, and every pocket fills with the card and its live price. The whole binder gets a link you can show anyone. Sell cards for friends at shows? Beltstra keeps the ledger: whose card sold, for how much, what you owe them, what you paid, and one tap to list it on eBay. Scan one card free with no account. Free plan is 300 scans a month; Pro is $29/month.
Enrichment
- Theme
- hobby collectibles and gaming tools
- Vertical
- Retail & commerce
- Function
- Search & retrieval
- Audience
- Prosumer
- AI stance
- AI-native
- Project type
- Commercial product
- Normalized one-liner
- binder page trading card scanner and pricer
- Manually corrected
- False
Could you build this?
Partial While the ledger is standard CRUD, segmenting a multi-pocket binder photo, rectifying perspective, identifying 9+ trading cards accurately, and fetching live market pricing requires tailored computer vision and card database matching.
What it would actually take: The stack would involve an OpenCV/YOLO-based pipeline trained to detect card sleeves, rectify geometric distortion, and extract individual card crops, followed by feature matching or embedding search against an extensive trading card image database (e.g., TCGPlayer, Cardmarket). Real-time price aggregators would then pull pricing data. The hard part is accurate multi-card detection under varying lighting and reflections coupled with a fine-grained image retrieval model for visually similar card variations.
Competitors
Other products that read as similar to this one — 276 launches clear the similarity bar, closest 8 shown.
Attention rank: #31 of 277 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 270 days after the earliest competitor.
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Other launches for this product
- No other launches for this product.