Azure AI Form Recognizer extracts information from structured and semi-structured documents. A custom model in Form Recognizer allows an organization to train the system on its specific document layouts and data fields.

As per the AI-900 study guide, a key advantage of a custom model is its flexibility. It can be trained with a set of labeled examples (e.g., invoices, purchase orders, receipts) that match the company’s format. Once trained, the model learns where to locate and extract fields such as invoice numbers, dates, or totals—regardless of layout differences between form types.

Option B is correct because a custom model can be trained to recognize a variety of form types, making it adaptable for diverse business processes.

Options A, C, and D are incorrect:

A: Both prebuilt and custom models are cloud-based; on-premises deployment is not an exclusive feature.

C: Custom models are not cheaper; they may involve additional training costs.

D: Custom models do not always guarantee higher accuracy—accuracy depends on the training data quality.