Context Engineering with SAP HANA Cloud Vector Engine — Building the AI Memory Layer

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Junaid Ahmed

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English

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Intermediate

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This article makes the case that context is the most critical asset in an enterprise AI system. Stale, ungoverned, and missing context leads to inaccurate AI responses regardless of how capable the model is. To demonstrate this, the article builds a complete context store on SAP HANA Cloud Vector Engine with document ingestion, embedding, and search functions. It then resolves the context staleness problem through context store lifecycle operations. Finally, a complete pipeline queries the Claude LLM and returns a grounded, cited response.

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Junaid Ahmed More about the author

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