The correct option is Add the new contract layout to the existing training set and retrain the custom model.

This approach is correct because adding labeled examples for the new contract layout and retraining the custom model lets the model learn the new structure while preserving the knowledge it already has. Retraining the existing model is usually the least disruptive choice when you need to support one more layout because the application can continue to call the same model endpoint and you avoid building extra routing logic or new integrations.

Lower the application accuracy threshold is incorrect because lowering the acceptance threshold does not add any support for the new layout and it reduces the reliability of classification rather than solving the underlying coverage gap.

Switch to the Azure prebuilt Document Intelligence contract model is incorrect because prebuilt models may not cover organization specific or uncommon contract layouts and they offer less flexibility for custom fields or labels. Using a prebuilt model could require additional validation and may not meet the firm specific extraction needs.

Create a separate training set for the new layout and train a new custom model is incorrect for this scenario because it adds more development and operational overhead. Running and maintaining multiple custom models requires extra routing logic and increases maintenance burden, so it does not meet the requirement to minimize development effort.

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