91 place 3

359 The 'last-mile' data problem is stalling enterprise agentic AI — 'golden pipelines' aim to fix it

VentureBeat
VentureBeat · 02/19/2026 08:00 EDT

Traditional ETL tools like dbt or Fivetran prepare data for reporting: structured analytics and dashboards with stable schemas. AI applications need something different: preparing messy, evolving operational data for model inference in real-time. Empromptu calls this distinction "inference integrity" versus "reporting integrity." Instead of treating data preparation as a separate discipline, golden pipelines integrate normalization directly into the AI application workflow, collapsing what typically require

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