A lot of "AI-powered" collector apps are just a wrapper around someone else's chatbot. AI Trade Collector is different — we built and trained our own card-reading AI from scratch, so it actually knows what a trading card looks like.
The card-orientation AI isn't something we downloaded off the shelf. We built it ourselves: we ran real cards through a real scanner, checked every single answer by hand, taught the AI using that, and shipped the result inside the app.
Then we had the AI double-check its own homework — flagging every card where it disagreed with us — and went through each flag by hand. It caught real mistakes we'd missed. It also raised a few false alarms we overruled.
That back-and-forth is the whole point. Chasing down disagreements is how you catch the quiet mistakes a simple pass/fail score would never show you.
And we don't stop there. The AI in the version you install today isn't the one we started with — it's been retrained on a bigger, more carefully checked set of cards than the version before it. Every batch of cards we scan adds to that pool. When we noticed an earlier version struggled with certain card types, we went out, gathered more of exactly those cards, and taught it again. Each new version starts from more than the last one did.
Each of the six checks is built to catch exactly one kind of mistake. Nothing gets trusted until it's confident in itself, or gets double-checked by a different step — so an error anywhere gets caught before it ever reaches your catalog.
Scan a card upside down and everything read off it afterward comes out garbled — names, numbers, all of it. WeightedScore checks which way a card is facing three separate ways before committing: an AI trained to recognize card layouts, a check for faces and portraits, and a look at where the fine printed detail actually sits. One answer has to clearly win, or the card gets set aside for you to check instead of a guess going into your catalog. Correct it later, and everything that depended on it updates automatically.
A shiny foil front and a dense, text-heavy back are two very different reading problems. Adaptive OCR — the technology that turns a photo of text into actual words — starts with a fast reader that clears a plain back in a few seconds, then calls in a slower, sharper reader for foil fronts and other tricky surfaces. That extra pass is a simple on/off switch in Settings, and it's already built into the app — nothing to install.
Some sets print a player's name sideways, or tucked into an odd corner, on purpose — that's just how that set was designed, not a scanning mistake. PrintMemory learns each set's own layout quirks from the cards you actually scan, so an unusual-but-correct placement stops looking like an error and starts reading as normal for that set.
Whatever proposes a card's identity — the built-in matching, or an AI model if you've turned one on — that guess still has to earn its place. ProofRead breaks down the text actually printed on the card, checks candidate names against a large roster of real players, and can even fix a name the scan garbled, like a dropped letter, by finding the closest real match. A name that isn't backed up by the card's own text loses to one that is.
Scan the same card twice — on purpose or by accident — and CardDNA is what catches it. Every scan gets turned into a compact visual fingerprint, not a copy of the photo, and that's enough on its own to spot a duplicate and match up two scans of the same physical card, all without the image ever leaving your computer.
One bad entry is all it takes to make a catalog untrustworthy. SafeGuard won't save anything below a minimum confidence level, and even a result that clears that bar still gets double-checked by a separate, unrelated step before it's trusted. Fail that check, and the save is undone automatically. If nothing's confident enough, the card is left alone rather than filled in with a guess.
A chatbot-style AI model is optional here — not something you need to get an accurate catalog. Out of the box, AI Trade Collector runs on Built-in: all six checks run in full, and no AI language model is involved at all. Cards get identified through instant matching against known card designs instead. Turning on a language model is something you choose to do, not something you're stuck figuring out by default.
| Built-in (default) | Ollama | Claude | OpenAI | |
|---|---|---|---|---|
| Where it runs | No model used | On your computer | Claude's servers | OpenAI's servers |
| Setup required | None | None | Your API key | Your API key |
| Works offline | ✓ | ✓ | — | — |
| Sends card data to an AI provider | No | No | Text + a small photo | Text + a small photo |
| Account required | No | No | Bring your own key | Bring your own key |
| Card identification | Instant matching | ✓ | ✓ | ✓ |
| Comp review | Price-range checks | ✓ | ✓ | ✓ |
| Comp photo verification | — | ✓ | ✓ | ✓ |
Switch to Ollama and a small AI model built into the app takes over identification, comp review, and photo verification — figuring out player, team, year, and set even from messy or hard-to-read text, flagging comps that don't belong, and confirming a listing photo actually matches your card. Since the model ships inside the app, none of this needs an account, a key, or anything extra to download.
Already run Ollama yourself? The app uses your copy too, as a second opinion on anything the bundled model isn't confident about.
Identification, comp review, and comp photo verification all draw on whichever AI Provider you've selected in Settings — Built-in, Ollama, Claude, or OpenAI. Pick one, and all three jobs use it — there's nothing to configure per task.
Want Claude's or OpenAI's full reasoning on the hardest cases instead of the bundled model? Switching providers is one click in Settings, with your own API key.
A plain-English rundown of what happens on your own computer, and what the app sends out only if you turn on the optional online price-lookup feature.
Your app doesn't go fetching listings from marketplaces or search engines itself. The comps server does that lookup centrally and hands back the result.
Market comps has a single master switch in Settings. Turn it off and the app stops contacting the comps server — no comp lookups, no shared identification, nothing.
That ID code is just a tiny scrap of data — far smaller than a photo — enough to recognize the same card printing again, but nowhere near enough to rebuild an image from.
Identifying one card is easy. Running thousands of them through six separate checks, on your own computer, without freezing the machine or losing your progress halfway through — that's the hard part, and it's where we put the real engineering effort.
Scanning a full deck is a start-it-and-walk-away job. Six checks running on every card adds up, so a big batch can take a few hours — start it after dinner, or let it run while you sort the next box, and come back to a finished catalog. It saves its progress as it goes, so you can close the app any time and pick up right where you left off.
The app processes several cards at the same time, automatically sizing itself to your computer's processing power when it starts. A faster computer works through more cards at once — nothing for you to configure.
Left unchecked, six checks running on many cards at once would try to grab every bit of your computer's power and bog everything down. So we deliberately cap how much it takes at once — meaning you can still use your computer normally while a batch runs in the background.
Looking up a card's market price takes an internet connection and a moment to come back, so that lookup happens in the background instead of pausing everything else. Identification keeps moving through your stack while price lookups catch up behind it.
The AI stays loaded and ready between cards instead of starting fresh for every single scan, which keeps things fast. If it sits idle for a while, it shuts itself down to free up memory for whatever else you're doing.
The app remembers exactly how far it got on every single card. Close it in the middle of a big batch, reopen it later, and it picks up right where it left off — it never starts over from scratch.
If a single card ever gets stuck or takes far too long, the app automatically sets it aside with a note and moves on to the next one instead of freezing the whole batch. Anything it already figured out is saved, so nothing gets redone later.
Plenty of tools in this space imply more than they deliver. Here's where our line is, so nothing surprises you after you install it.
There's no centering, corner, edge or surface analysis, and no numeric grade. The app deliberately ignores condition — graded slabs are filtered out of comps so a PSA 10 sale doesn't distort what your raw copy is worth.
It works from the scans your scanner's own software already produced, and only rotates them in quarter turns — it doesn't straighten a crooked scan or crop the image for you.
Baseball is the deepest — that's where the player-name verification and the bulk of the training scans live. Pokémon was added deliberately after we identified the gap. Other sports and TCGs are read and cataloged, but with less specialized support behind them.
Our custom-trained orientation AI and the built-in language model are available on Windows right now. The app itself runs on macOS and Linux too, just without those two extras for the moment.
Any accuracy numbers we mention were measured on cards the AI had never seen before, using our own scans. That's real, but it's not a guarantee about your specific collection — lighting, sleeves, and how a particular set is printed can all affect the results. That's exactly why the system is built to catch its own mistakes: no single check is right every time.
Point it at a folder of scans and watch the whole process work — everything on this page is in the version you download.