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Data Ingestion & Orchestration Workflow We begin by aggregating content from a curated list of trusted news sources via RSS (in XML or JSON formats). For each feed, we extract key metadata—headline, URL, publish date, and summary—and normalize these into a unified schema to ensure consistency across sources. Once ingested, articles are deduplicated based on identifiers like URL or title, removing overlaps across feeds and ensuring uniqueness. The normalized and deduplicated articles are then distributed through Zerve’s spread() fleet, enabling parallelized downstream processing for tasks like summarization, sentiment analysis, and entity extraction. This orchestrated fan-out model ensures the workflow remains scalable, fault-tolerant, and fast, even under sudden influxes of news.