Knowledge Graph Engineering for Industrial and Enterprise AI
Short answer. A knowledge graph connects assets, locations, events, sensors, models, procedures and outcomes as explicit relationships. AgenticNex AI designs ontologies and builds knowledge graphs on Neo4j or RDF stores, so analytics and AI can reason over context and every recommendation links to its evidence.
What is the business problem?
Context that engineers carry in their heads, such as which formation a well is in, which sensor feeds which model, which procedure applies, is not stored anywhere a system can use.
Why can conventional approaches be insufficient?
- Relational schemas struggle with highly connected, evolving context.
- Vector search finds similar text but not explicit relationships.
- Without lineage from evidence to advice, recommendations cannot be audited.
What is our engineering approach?
- Model the domain ontology with subject-matter experts.
- Populate the graph from operational, document and model sources.
- Expose graph queries and graph-based retrieval to analytics and GenAI.
- Record advisories, actions and outcomes back into the graph.
What does the architecture look like?
Which technology capabilities are involved?
- Neo4j and RDF / GraphDB
- Ontology design (OWL, SKOS)
- Entity extraction from documents
- GraphRAG for GenAI
- Graph analytics and similarity
- Lineage from evidence to decision
Example use cases
- Drilling knowledge graph: basin, formation, well, event
- Railway asset knowledge graph
- Clinical knowledge systems
- Similar-event and similar-asset discovery
Expected business and technical outcomes
- Context available to every model and user
- Recommendations linked to evidence
- Faster discovery of similar past events
- [Insert verified project result]
Relevant case studies
Frequently asked questions
Neo4j or RDF?
Neo4j suits operational, query-heavy graphs; RDF stores suit standards-based, inference-heavy ontologies. The choice follows the use case.
How does a knowledge graph improve GenAI?
Graph retrieval gives the model explicit relationships and provenance, which improves multi-step answers and makes them auditable.
Related insights
Knowledge Graphs for Oil & Gas
A knowledge graph for oil & gas connects country, basin, formation, well, event, sensor, feature, model, risk, advisory, procedure, action and outcome as explicit relationships.
Knowledge GraphsKnowledge Graph + AI for Industrial Asset Intelligence
Combining a knowledge graph with AI gives industrial asset intelligence both context and prediction.
Architecture GuidesRailway Asset Knowledge Graph Architecture
A railway asset knowledge graph links routes, sections, track, structures, OHE, signalling, rolling stock, sensors, inspections, defects and work orders.
IndustryMaritime
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