Breaking the Enterprise AI Bottleneck: How Dify Knowledge Pipeline Transforms Unstructured Data into Actionable LLM Context
In enterprise AI implementations, the bottleneck rarely lies in the model itself—it’s in context engineering. Vast volumes of business-critical data are trapped in unstructured formats: PDFs, PPTs, Excel spreadsheets, images, and HTML files. The ability to reliably convert scattered, heterogeneous, and constantly updated enterprise data into LLM-recognizable context is the make-or-break step for successful AI adoption.