Your examples.
Your AI, at work.

Build a support-ticket model, step by step. 900 labelled support tickets · 6 categories Step 1 · Set up. Name the model and say what it should predict. Step 2 · Upload. Upload the spreadsheet you already keep: CSV, Excel or JSON. It finds the column to predict, and counts the rows and categories. It measures which columns carry signal: the message is read, the ticket ID left out. Check the rows exactly as the model will read them. Step 3 · Data quality. The data quality report: 853 usable rows across 6 categories. Personal information is found before training: email addresses and phone numbers. Mask it with one click. It is masked the same way in everything the model reads later. Step 4 · Train. Choose the model. An AI Classifier Model reads meaning and trains in about a minute. Training runs in the background. You can close the page. Step 5 · Validate. Tested on 127 tickets it never trained on: 92.1%, against an 18.1% naive baseline. Accuracy for every category, weakest first. Every mistake is listed. If the label was wrong, correct it for the next training. Publish the version to start using it. Step 6 · Use it. Try a record and see the answer with its confidence. Fill a spreadsheet: upload 200 new tickets. All 200 rows filled, ready to download. Every row gets a predicted category and a confidence score. Or call the model from your own code with a workspace API key. Need more? Train a Dedicated AI Model on the same data, on GPUs, and compare. Your categories, learned from your examples. amt.staycharted.com

Sort product photos with Vision. 120 product photos · 4 categories Step 1 · Set up. Name the model and choose Pictures. Step 2 · Upload. Add a ZIP with one folder per category, or a spreadsheet of picture links. The ZIP: caps, mugs, t-shirts and tote bags, 30 pictures each. The categories come from the folder names. Step 3 · Check. Every picture is checked and its location data removed. Near-duplicate pictures are found, so one photo isn't counted twice. Keep one of each with a click: 110 pictures, ready to train. Look through every picture by category. Change a category or leave one out. Step 4 · Train. Choose the AI Image Classifier Model. It trains in about a minute. Step 5 · Validate. 16 of 16 test pictures right. Results depend on your own pictures. Step 6 · Use it. Sort the new arrivals: upload a ZIP of 24 new pictures. All 24 filled, ready to download. Every picture gets a category and a confidence. Sort pictures the way your team already does. The Vision add-on · amt.staycharted.com