STAYCHARTED AMT / INSIGHTS
How AI Model Trainer works behind the scenes
Explore the design decisions behind AMT’s text classifiers and personal-information checks.
Understand what the model reads
Text can carry both distinctive words and meaning. Learn why AMT combines those signals for AI Classifier Models and how that differs from fine-tuning a Dedicated AI Model. Use the explanation to decide what to test on your own examples.
Understand what masking changes
Learn which patterns AMT checks before training, how masking applies to new text, and what it can miss. A masking choice changes model inputs; it does not erase original uploads or remove information an older model already learned.
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Try it on your own examples.
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