Most journalists use AI tools one-at-a-time: write a draft, run it through a fact-checker, generate metadata. But AI APIs support batch processing — running multiple articles through the same workflow simultaneously. A newsroom that batch-processes its daily article queue at 6am has all articles fact-checked, metadata-generated, and social snippets drafted before the editorial team arrives.
Batch Processing Architecture
Trigger: Articles submitted to CMS with "ready for AI processing" status. Queue: A simple job queue (AWS SQS, Redis) collects submitted articles. Processing: At 5:30am, the batch processor pulls all queued articles and runs each concurrently through: fact-checking API (Omniscient AI), metadata generation (OpenAI), social snippet generation (OpenAI), and readability check. Output: Each article returns to the CMS with: fact-check results attached, draft metadata populated, social snippets drafted, and readability score displayed. Editors review at 6am with all AI processing already complete. Cost per article: approximately $0.05–$0.15 in API costs.