Computable Contextual Knowledge Graph for Industrial Intelligence
The knowledge foundation behind Facilities of the Future. One computable model built from your existing documents - P&IDs, ISOs, data sheets, and operational data.
Book a DemoFrom Disconnected Engineering Documents to a Connected, Computable Facility
The Contextual Knowledge Graph bridges the gap between how engineering knowledge is stored today and how AI needs it structured to be useful.
From Paper to a Facility That Thinks
Cross Documents Relationship Mapping
Drishya AI's Computable Contextual Graph maps how documents reference each other - which P&ID references which Data Sheet, which standards govern which designs, which Isometrics derive from which P&IDs - building a map of engineering relationships.
Cross-Discipline Connections
The Graph connects process engineering to piping, piping to instrumentation, instrumentation to control logic, and control logic to safety systems - so a change in one discipline is immediately visible across every other.
Hierarchy & Topology Construction
From a single set of P&IDs, the Graph extracts the full equipment hierarchy, maps every process connection, identifies every control loop, and builds a navigable topology of your entire facility - automatically and accurately.
Version & Revision Tracking
Every engineering document goes through revisions. The Contextual Graph tracks every version of every P&ID, ISO, and Data Sheet - so you always know which revision is current, whaat changed, when it changed, and what downstream documents are affected.
Automatic Change Propagation
When a design change hits one document, the Contextual Graph traces every downstream impact automatically - identifying which ISOs, data sheets, deliverables, and operational parameters need to be updated, before the change becomes an inconsistency.
AI Reasoning Foundation
Generic AI runs on generic data and produces generic answers. The Contextual Graph gives AI the engineering structure it needs - equipment relationships, process topology, design constraints, and operational context - to reason about your specific facility.
Cross Documents Relationship Mapping
Drishya AI's Computable Contextual Graph maps how documents reference each other - which P&ID references which Data Sheet, which standards govern which designs, which Isometrics derive from which P&IDs - building a map of engineering relationships.
Cross-Discipline Connections
The Graph connects process engineering to piping, piping to instrumentation, instrumentation to control logic, and control logic to safety systems - so a change in one discipline is immediately visible across every other.
Hierarchy & Topology Construction
From a single set of P&IDs, the Graph extracts the full equipment hierarchy, maps every process connection, identifies every control loop, and builds a navigable topology of your entire facility - automatically and accurately.
Version & Revision Tracking
Every engineering document goes through revisions. The Contextual Graph tracks every version of every P&ID, ISO, and Data Sheet - so you always know which revision is current, whaat changed, when it changed, and what downstream documents are affected.
Automatic Change Propagation
When a design change hits one document, the Contextual Graph traces every downstream impact automatically - identifying which ISOs, data sheets, deliverables, and operational parameters need to be updated, before the change becomes an inconsistency.
AI Reasoning Foundation
Generic AI runs on generic data and produces generic answers. The Contextual Graph gives AI the engineering structure it needs - equipment relationships, process topology, design constraints, and operational context - to reason about your specific facility.
The Knowledge Layers Behind Computable Facilities That Think
The Contextual Graph is built in layers, each extracting a different dimension of your facility's operations and intelligence from the documents and data you already have.
Cross Layer Intelligence Which
Powers Drishya AI
The Contextual Knowledge Graph is the foundation that powers Drishya AI products unlocking value across the different phases of the asset lifecycle.
Artisan
Intelligent document processing and content creation.
- P&ID and Isometric Digitization from PDFs to Smart Diagrams.
- Automated HYSYS Flowsheet Generation in 3 Days.
- 100+ Deliverable Fabrication Pack Generation in 10 Minutes.
- Isometric QC Against P&IDs and LDTs.
- Engineering Deliverables on Demand.
Brains
Advanced reasoning and decision-making engine.
- Predictive Asset Health with 15+ Hours Early Warning.
- Realtime Monitoring, Diagnosis and Optimization.
- ISA-8.2 Compliant Alarm Intelligence.
- Intelligent Soft Sensors & Virtual Meters.
- Anomaly Detection Grounded in Engineering Context.
- Condition Based Maintenance for Rotating Assets.
- Pipeline Leak Detection & Localization.
Junior
Lightweight AI Assistant for everyday tasks.
- Natural Language Queries Across Your Entire Plant Model.
- Tag-Level, Valve-Level, Sensor-Level Answer Precision.
- Engineering Workflow Automation from Single Prompts.
- Cross Document Navigation Across P&IDs, ISOs, and Data Sheets.
- Zero Hallucination - Grounded in Your Contextual Graph.
- Agentic Task Execution for Multi-Step Engineering Workflows.
Frequently Asked Questions
Technical questions about the Contextual Graph architecture.
Ready to Convert Your Engineering Drawings & Documents into Contextual Intelligence?
See what happens when every document, every discipline, and every phase of your facility becomes computable.
- Turn thousands of static PDFs into one queryable, computable model.
- Connect every P&ID, ISO, and data sheet into a single knowledge layer.
- Give your AI the structured engineering foundation it actually needs.
- Replace months of manual cross-referencing with seconds of graph queries.
- Go from disconnected documents to a connected, computable facility in weeks.