See what your documents actually contain.
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.
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.
Without a proper ontology, extracted tag data from a P&ID does not map to the equipment hierarchy in SAP PM. BOM items from a drawing do not align with your procurement system's part structure. Instrument data from a datasheet does not flow into your CMMS predictive-maintenance model. Ontologies define how tag registers, equipment hierarchies, BOM trees, and process relationships are structured, ensuring extracted data has a destination in your enterprise systems and does not require months of manual data modelling. For EPC handover and digital-twin population specifically, ontology alignment is the difference between Day 1 operational readiness and a 6-18 month post-handover reconciliation project.
Eleven standards supported natively. Core: ISA 5.1 (P&ID symbology), ISA 5.4 (instrument loop diagrams), ISA 88 (batch process control), ASME B31.3 (process piping), ASME B31.1 (power piping), ASME Section IX (welding / welder qualification). Industrial data integration: ISO 15926 (oil & gas data integration), DEXPI (Data Exchange in Process Industry, XML format), CFIHOS 2.0 (Capital Facilities Information Handover Specification). Reliability / structuring: ISO 14224 (equipment reliability data), IEC 61346 (industrial systems structuring). Quality: AIAG FMEA 4th / 5th edition, AIAG-VDA harmonised. Indian regulatory: IBR 1950, OISD 118, PESO / Petroleum Rules 2002, CCOE. Custom extensions for OEM-specific and site-specific naming conventions available.
Yes. Pathnovo's ontologies are configurable to match your existing SAP PM functional location hierarchy, IBM Maximo asset structure, AVEVA AIM / NET data model, Hexagon SDx / SmartPlant object classes, Bentley iTwin asset hierarchy, Cognite Data Fusion knowledge graph, or any proprietary equipment classification system. We map your naming conventions, tag numbering rules, equipment groupings, and hierarchical relationships into the ontology so extracted data flows directly into your system without transformation. Custom ontology configuration is included at project kickoff at no additional fee.
DEXPI (Data Exchange in the Process Industry) is an open XML-based data-exchange standard developed by the DEXPI Initiative, a consortium of owner-operators (BASF, Bayer, Shell, BP, Equinor) and software vendors (AVEVA, Hexagon, Siemens). DEXPI provides a vendor-neutral format for exchanging P&ID data across engineering tools. Pathnovo's extraction output is DEXPI-compliant natively, which means extracted P&ID data flows seamlessly between AVEVA P&ID, Hexagon SmartPlant P&ID, Siemens COMOS, Bentley OpenPlant, and any DEXPI-aware downstream system. See /alternatives/pnid-io for the DEXPI-specific competitor context.
CFIHOS (Capital Facilities Information Handover Specification) is the industrial data standard developed by USPI (Process Industry Practice) and IOGP (International Association of Oil & Gas Producers) for capital-project handover between EPC contractors and owner-operators. It defines object classes, attributes, and relationships for engineering data: the exact structure most modern digital twins expect. Pathnovo's extraction output is CFIHOS 2.0-aligned natively, so data flows into AVEVA AIM, Cognite Data Fusion, Bentley iTwin, Hexagon HxGN SDx, and enterprise digital twins without a middle translation layer. For Aramco, QatarEnergy, ADNOC, PETRONAS, and other operators mandating CFIHOS-compliant handover, this is decisive. See /solutions/engineering-handover and /solutions/digital-twin-data-integration.
Indian regulatory ontologies are first-class data models in Pathnovo's extraction engine. IBR Form IV register structure, OISD 118 HAZOP register format with inter-distance tables (Chapter 3), PESO Form XIV / XV licence scope, CCOE competent person and licence condition models: all encoded. Extracted engineering data automatically populates compliance registers in each regulatory format concurrently. One extraction, four regulatory views. No competing software product encodes these Indian regulatory ontologies; see /compliance/indian-epc-compliance-bundle for the integrated workflow.
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.
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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.