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Most enterprise AI projects do not fail because the model is bad. They fail because the data feeding it is a mess: broken pipelines, mismatched systems, and context locked in one engineer’s head. Upriver, an Israeli startup, has raised $14M to automate the cleanup, betting that this dull but critical layer is where the AI […]
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<p>An enterprise AI agent answers with total confidence, but the number is wrong. Nobody catches it until someone traces it back to a stale metric definition or a document the retrieval system n [...]
<p>Across 101 enterprises, the infrastructure that feeds AI agents their business context is being built faster than it can be trusted. Retrieval-augmented generation is already the default cont [...]
<p>Enterprise AI agents have a new production failure mode, and it is not the model. As enterprises move from single-layer RAG to hybrid retrieval architectures, the same underlying data produce [...]