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Oil & Gas is ready for agentic transformation -- but only if the foundation is right

Most AI initiatives in oil & gas fail because they bolt intelligence onto broken processes and disconnected data.

Most AI initiatives in oil & gas fail because they bolt intelligence onto broken processes and disconnected data.

The Alphient approach is different. With Prime (pro-code) and Prime (low-code), we start with three pillars:

Structured Knowledge

  • Segment P&L by basin, asset class, and contract type
  • Basin Revenue Repo
  • Segment P&L Store

Automated Process Packs

  • Automated revenue attribution across the integrated value chain
  • Revenue Attribution Flow

Intelligent AI Agents

  • Segment Analyst Agent
  • Revenue Mix Monitor
  • Trading P&L Bot

The business questions this unlocks:

  • Revenue Mix
  • Lifting Cost
  • Rig Utilisation
  • Exploration Speed
  • AI Operations

AI agents for revenue mix, lifting cost, rig utilisation, and value chain management.

Knowledge. Process. Agents. That is the transformation formula.

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