Question

An insurance company wants to automatically extract structured fields (policy number, claimant name, dates, and dollar amounts) from millions of scanned claim forms and unstructured PDFs. The team has no ML engineers and needs a solution that requires no model training, returns structured key-value pairs, and can scale to process large batches. Which Google Cloud approach best meets these requirements with the least operational effort?

Accepted Answer

Use Document AI with a prebuilt or specialized processor to parse the forms and return structured entities and key-value pairs.

Answer

Train a custom Vertex AI AutoML text classification model on labeled samples of the claim forms.

Answer

Use the Cloud Vision API OCR to extract raw text, then write custom regex-based parsing in a Cloud Function to derive fields.

Answer

Deploy an open-source OCR model on a GKE cluster with GPUs and build a custom entity extraction pipeline.