Send us 10 documents from your current project. We extract, reconcile, and show you exactly what we find in 48 hours, before any contract.
If the accuracy isn't what we promised, you owe us nothing.
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Pre-built schemas for tag registers, equipment hierarchies, BOM trees, and EPC site structures. Map your engineering data to structured ontologies that fit your domain without starting from scratch.
Send us 10 documents from your current project. We extract, reconcile, and show you exactly what we find in 48 hours, before any contract.
If the accuracy isn't what we promised, you owe us nothing.
Extracted data is only useful if it maps to something your systems understand. Without a proper ontology, tag data from a P&ID doesn't match the equipment hierarchy in SAP PM. BOM items from a drawing don't align with your procurement system's part structure. We provide pre-built, standards-aligned schemas so your extracted data has a home and you don't spend months building data models from scratch.
Structured schemas that define how engineering data is organized — tag hierarchies, equipment classes, BOM trees, facility structures. They ensure your extracted data maps correctly to your systems.
No. We provide pre-built schemas for tag registers, equipment hierarchies, BOM trees, and EPC site structures. You extend them with your naming conventions and custom attributes.
ISO 15926, ISA 88, IEC 61346, and industry-standard equipment classification systems. We map to your specific enterprise system schema.
Yes. A single ontology can have system-specific field mappings for SAP PM, Maximo, AVEVA, Teamcenter, and any custom system. Extract once, deliver to many.
Pre-built ontologies are configured in 1-2 weeks. Custom ontologies for domain-specific needs take 3-6 weeks depending on complexity.
Yes. Ontologies are extensible. Add new attributes, modify hierarchies, or add new equipment classes without rebuilding from scratch.
We build normalisation rules into the ontology. Different naming conventions from different teams all map to the same canonical structure.
Ontologies are the bridge. They define the engineering data model, then system-specific field mappings translate it to SAP functional locations, Maximo asset hierarchies, etc.
Yes. If your organisation uses a proprietary classification system, we map it into the ontology alongside standard classifications.
Yes. Facility ontologies support hierarchies across sites, plants, units, areas, and systems. Each level can have its own attributes and relationships.
Each tag and equipment entry in the ontology links to applicable standards, inspection requirements, and compliance status. Agents use this for automated compliance checking.
We update the ontology to reflect new standard revisions. Existing data is re-validated against the updated ontology and non-conformances flagged.
Yes. Multi-level BOMs in the ontology track revision per component, alternate parts, effectivity dates, and make/buy designations.
Full documentation including data dictionaries, relationship maps, field definitions, and system mapping specifications. Your team can maintain and extend independently.
With a proper ontology, you can query by tag, equipment class, system, area, or any attribute. Relationships between documents and tags are explicit, not implicit.