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A detailed guide on optimizing knowledge graph ingestion for AI agents, presenting a five-step pipeline (extraction, resolution, embedding, deduplication, routing) to prevent graph corruption and improve retrieval quality.
This blog post describes the architecture for a scalable ingestion pipeline using Temporal to handle crawling, extracting, chunking, and embedding customer documentation from various sources, emphasizing durability, statefulness, and concurrency control.