Knowledge Graph RAG.
The Context Moat.
While Vector RAG finds similar text, GraphRAG understands relationships. This is how Hagonel achieves true "Institutional Memory."
The Limitation
Vector RAG Can't Reason
Standard Retrieval-Augmented Generation relies on semantic similarity—finding documents with matching keywords. But enterprise questions require understanding relationships and hierarchy.
Example Failure
"Who is the decision-maker for the Q1 audit, and how does their budget interact with the marketing spend?"
Vector RAG sees these as disparate text chunks. It cannot traverse the relationship between the decision-maker → their authority → the budget allocation → the marketing dependency.
Accuracy Comparison
Source: Industry benchmarks for complex enterprise domain queries
The Architecture
How Knowledge Graphs Enable Reasoning
Instead of chunks of text, Hagonel maps your business as entities and relationships— a traversable graph that mirrors how humans think about organizations.
Entity Extraction
Hagonel identifies Entities: People, Projects, Budgets, Tools, Documents. Each becomes a node in the graph with typed properties.
Relationship Mapping
Connections are typed: "manages," "approves," "depends_on," "funds." This creates traversable Edges that encode business logic.
Graph Traversal
Queries traverse multiple hops: Person → manages → Project → depends_on → Budget → approved_by → Person. Multi-hop reasoning unlocks true intelligence.
Vector RAG vs. Knowledge Graph
A detailed comparison for enterprise "Institutional Memory"
| Feature | Vector RAG | GraphRAG (Hagonel) |
|---|---|---|
| Retrieval Method | Semantic Similarity | Relationship Traversal |
| Complex Query Accuracy | 60-70% | >90% |
| Setup Complexity | Low (Plug & Play) | Higher (Ontology Modeling) |
| Explainability | Low ("Black Box") | High (Traceable Paths) |
| Multi-Hop Reasoning | Not Supported | Native Support |
| Regulatory Compliance | Difficult to audit | EU AI Act Ready |
Strategic Advantage
Context is the New Moat.
Generic LLMs can be fine-tuned, but they cannot replicate your specific business relationships. The Knowledge Graph Hagonel builds for your organization becomes proprietary intelligence that grows more valuable over time.
Entity Resolution
"J. Doe" in Slack → "John Doe" in HRIS → "JD" in email signatures. One identity.
Ontology Mapping
Your vocabulary, your hierarchy, your processes. Encoded as structured knowledge.
Temporal Memory
Not just what exists, but what changed, when, and why. Full historical context.
Ready to Build Your Context Moat?
Hagonel's Knowledge Graph starts learning your business from day one. The longer it runs, the deeper the institutional memory.
View Pricing