You are building a structured data extraction system using Claude. The system extracts information from…

Question

You are building a structured data extraction system using Claude. The system extracts information from unstructured documents, validates the output using JavaScript Object Notation (JSON) schemas, and maintains high accuracy. It must handle edge cases gracefully and integrate with downstream systems.

Your extraction system processes two document types: standard monthly reports (archived after processing) and urgent exception reports (must trigger business alerts within 30 minutes of receipt). Both use the same JSON schema. You want to minimize API costs while meeting latency requirements.

How should you architect the processing pipeline?

Accepted Answer

D. Route standard reports to the Batch API for 50% cost savings, and route urgent exception reports to the real-time Messages API.

Answer

A. Submit all documents to the Batch API with custom_ids for tracking. When results arrive, immediately process urgent documents and trigger delayed alerts for exceptions.

Answer

B. Queue all documents and submit hourly batches, flagging urgent documents for expedited handling when batch results return.

Answer

C. Submit all documents to the real-time Messages API to ensure consistent processing latency across document types.

Question 111