Adaptive Ontology is metricsIQ’s methodology for creating shared business context across data, systems, and workflows. Without it, agents cannot find or understand the data they need.
The Problem It Solves
A well intervention solution integrating 5+ systems needs a shared vocabulary: What is a “well”? What does “decline rate” mean across production data, reservoir models, and economic systems? Adaptive Ontology answers these questions – and adapts as the business changes.
Why “Adaptive”
Traditional ontologies are brittle. Business vocabularies shift over time – new equipment types, reorganized business units, updated regulatory categories, acquired companies with different terminology. Static data models break when the business changes.
Adaptive Ontology uses agents to maintain the ontology dynamically as business context evolves, preventing the data breakages that derail most enterprise AI initiatives.
Architecture
The architecture is modular and extensible:
- Core modules: Time, location, measurement – the universal building blocks.
- Domain modules: Well, reservoir, pipeline, generation unit – industry-specific concepts.
- Company-specific extensions: Your terminology and rules – the layer that makes your ontology yours.
The Foundation Layer
In the three-layer AI architecture (foundation, execution, applications), Adaptive Ontology is the foundation. Above it sits agent execution (Decision Value Loops). At the top: business value.
Without the foundation, agents have nothing meaningful to work with. This is why so many enterprise AI projects fail – they build applications without the data foundation those applications require.