Knowledge Graph Engine Canonical URL: https://babadook.tech/modules/knowledge-graph-engine Entity: modules Content hash: 7705ce172e001d9b4d1cb4c6cd45aba85fc17aeb2d17e3684acdd3f786a6ec65 AI reads your documents and automatically maps the relationships between people, products, processes, and decisions — building a navigable knowledge graph that your entire organization can explore and query. AI reads your documents and automatically maps the relationships between people, products, processes, and decisions — building a navigable knowledge graph that your entire organization can explore and query. your-documents-build-the-graph.-automatically. Your Documents Build the Graph. Automatically. As your teams write, AI extracts entities — people, organizations, products, concepts, events, locations, and technologies — and maps them into a navigable graph. No tagging. No manual categorization. The knowledge structure emerges from the work your people are already doing. The engine goes beyond explicit mentions. It discovers implied relationships across documents — connections that no single author would recognize because they span departments, projects, and years of institutional history. data Viz Knowledge Graph Capabilities - Entity Extraction: Real-time, as documents are written - Relationship Discovery: Explicit and implied connections across all content - Entity Types: 7 built-in + unlimited custom types - Graph Scale: 10M+ entities, 100M+ relationships - Visualization: Interactive 2D and 3D graph exploration - Querying: Natural language and structured graph queries - Validation: Semantic consistency checking across the entire graph What the Knowledge Graph Gives You subtitle: Transform years of documents into a navigable map of your organization's collective intelligence Zero-Effort Extraction desc: Entities are identified and linked in real-time as documents are created. No batch jobs, no manual tagging, no extra work for your teams. Hidden Connections desc: Discover relationships between projects, people, and decisions that span departments and years — connections invisible to any single team. Visual Exploration desc: Navigate your organization's knowledge as an interactive graph. Filter by entity type, time range, department, or project. Find paths between any two concepts. Semantic Integrity desc: Automated validation ensures your knowledge graph stays consistent as it grows — flagging contradictions, duplicates, and gaps. Knowledge Discovery Rate value: 340 timeframe: 6 months unit: percent increase Cross-Document Connections value: 12500 timeframe: per quarter unit: auto-discovered links Graph Scale Capacity value: 10000000 timeframe: nodes unit: with 100M+ edges content section value: Your teams are writing documents full of valuable relationships — between people, products, decisions, and systems — but those connections are invisible. MUKR's Knowledge Graph Engine reads your documents as they're written and automatically maps who is connected to what, which decisions affect which products, and where critical relationships exist that nobody knew about. features ontology: ATHENA inference: fullSET extraction: Prometheus NLP Section 1 Person Section 2 Organization Section 3 Product Section 4 Concept Section 5 Event Section 6 Location Section 7 Technology Relationships products - MUKR — https://babadook.tech/products/mukr industries - Defense Intelligence — https://babadook.tech/industries/defense-intelligence - Knowledge Management — https://babadook.tech/industries/knowledge-management - Research & Development — https://babadook.tech/industries/research-development capabilities - Epistemological Framework — https://babadook.tech/capabilities/epistemological-framework - Knowledge Graph — https://babadook.tech/capabilities/knowledge-graph sub modules - Intelligence Layer — https://babadook.tech/sub-modules/mukr-intelligence-layer use cases - Epistemological Knowledge - Knowledge Graphs business sizes - Enterprise - Government - Mid-Market