Successful adoption of AI agents requires context engineering. Context engineering requires access to data, metadata, process flow, and more. Context engineering ensures your data is ready for agentic ...
In an era defined by an unprecedented explosion of data and the transformative promise of AI, CIOs and enterprise IT leaders face a paramount challenge — how to truly harness their vast information ...
Actian’s Ole Olesen-Bagneux explains why AI agents need metadata, lineage, context, and governance before enterprises can trust them at scale.
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