Which is more popular?
CardGrade might be a bit more popular than Gitql. We know about 1 link to it since March 2021 and only 1 link to Gitql.
Website, pricing, platforms and company facts side by side.
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| Website | github.com | cardgrade.io |
| Pricing | — | |
| Platforms | — | |
| Company | — | Startup from the United States · 1 - 9 employees |
| Listed in |
In their own words, as submitted to SaaSHub.
No description of Gitql yet.
CardGrade helps trading-card collectors decide which cards are worth paying to grade. Upload front and back photos and CardGrade's CGI Vision AI performs a 16-zone inspection of every corner and edge, front and back, plus centering and surface. In about 60 seconds it returns predicted PSA, BGS,...
What each product offers, as listed by its team.
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An editorial look at what each product does well and who it suits.
Overall verdict
Why this product is good
Recommended for
No analysis of CardGrade yet.
How often each product is chosen within a category, 0–100% relative to the other.
As answered by people managing Gitql and CardGrade.
CardGrade's answer:
CardGrade combines a 47-point computer-vision inspection with predicted PSA, BGS, and CGC outcomes in about 60 seconds. Each report includes sub-scores, confidence, centering measurements, and a market-value estimate when available, so collectors can pre-screen cards before paying to submit them for professional grading. CardGrade is an independent prediction tool, not an official grading service.
CardGrade's answer:
CardGrade grew from TCG Treasury LLC’s focus on practical tools for trading-card collectors. The product was created to make pre-submission condition review faster and more consistent: upload front and back photos, receive a structured AI inspection, and decide which cards are worth sending to a professional grader.
CardGrade's answer:
Choose CardGrade when you want a fast, repeatable pre-screening workflow across Pokémon, sports cards, Magic: The Gathering, Yu-Gi-Oh!, One Piece, and other collectible cards. It combines front-and-back image analysis, four-pillar sub-scores, cross-company grade predictions, collection history, and optional market-value context in one workflow. Results are estimates, so they help prioritize submissions rather than replace professional grading.
CardGrade's answer:
CardGrade is built for collectors, card shops, dealers, and grading-prep workflows. It is useful for anyone who wants to identify centering, corner, edge, and surface issues before spending money and time on professional grading submissions.
CardGrade's answer:
CardGrade uses TypeScript-based web, mobile, and browser-extension clients, with React/Next.js and React Native/Expo surfaces backed by computer-vision and AI grading services. The system combines image capture, structured condition analysis, grade-prediction logic, account and collection workflows, and store-connected billing.
CardGrade's answer:
Customer names are not publicly disclosed.
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Recommendations tracked on public social media and blogs since March 2021.
How does this compare to https://github.com/filhodanuvem/gitql. Source: over 3 years ago
This is a write-up of how we structured the pipeline behind CardGrade, an app that pre-grades cards from phone photos. Its engine, CGI Vision AI, returns estimated PSA, BGS and CGC grades with confidence scores in about 60 seconds. It's... - Source: dev.to / 18 days ago
