PI Mapping Intelligence System

Overview

We delivered a multi-agent system that mapped PI points to physical equipment across SCADA, maintenance, and operational databases. This resolved inconsistent tag names and context gaps, resulting in a live knowledge graph that enhanced diagnostics, visibility, and automation.

Challenge

◼ Inconsistent Tag Naming: Equipment appears under different aliases in different systems, making entity resolution difficult.

◼ Manual Mapping Effort: Current mapping processes rely on tribal knowledge and manual workflows.

◼ Low Interoperability: Fragmented systems lack semantic alignment, limiting analytics and automation.

Solution

◼ Agent-to-Agent (A2A) Reasoning: Agents with self-reflection capabilities collaboratively resolve tag identities and context.

◼ NLP + Ontology Alignment: Extract and map tag descriptions using symbolic reasoning and domain ontologies.

◼ Continuous Refinement: Feedback loops enable live updates to mappings, improving accuracy over time.

Key Benefits

◼ Unified Equipment Intelligence: Seamless visibility across SCADA, maintenance, and operational databases.

◼ Automated Knowledge Graphs: Rich, evolving maps of equipment-tag relationships.

◼ Scalable Deployment: Adaptable to large, multi-system industrial environments.

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