AlgoDeploy vs Card AI
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
AlgoDeploy compared with Card AI
| Detail |
AlgoDeploy |
Card AI |
| What it does | Python algorithmic trading software for backtesting and live trading strategies on your own infrastructure
| Scan cards, know their value
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| Stage | Not given
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| Founded | Not given
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| Based in | US
| Not given
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| Pricing model | Not given
| Free
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| Pricing | Student (Free with valid .edu email), Starter ($99 one-time), Pro ($249 one-time), Quant ($499 one-time). Optional Maintenance & Community subscription: $10/mo or $100/year.
| Not given
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| Key features | - 11 built-in technical indicators
- Built-in Model Context Protocol (MCP) server for AI assistants
| - AI card recognition from photos
- Bulk scanning for multiple cards
- Price history and market trends
- Raw and graded card price comparison
- Collection portfolio value tracking
- Multi-game support including Pokemon, MTG, Yu-Gi-Oh and sports cards
- Wishlist and card-set browsing
- Search by card name, set or card number
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| What makes it different | - Self-hosted infrastructure with source code included — own your software forever with a one-time purchase
- Unified backtesting and live-trading engine — same code backtests and trades live
- No subscription required for the core product — lifetime license after one-time payment
- Your data and keys stay on your machine — no cloud lock-in or third-party data storage
| - Confirms exact card printing before pricing to ensure accuracy
- Separates raw card and graded card prices in different markets
- Tracks collection value over time with portfolio management
- Unified collection across multiple trading card games
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| Community votes | 0 | 0 |
| DR (Domain Rating by Ahrefs) | Not checked yet ● no change since last check | Not checked yet ● no change since last check |
| Trust Flow (Majestic) | 1 | 0 |
| Citation Flow (Majestic) | 22 | 0 |
| Referring domains (Majestic) | 19 | 0 |
3 details filled in for both companies.
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