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The Knowledge Graph option builds a Neo4j-backed graph from your documents instead of a flat vector index. Named entities become nodes. Relationships between entities become typed, directional edges. When an agent queries the graph, Lyzr translates the question into a Cypher traversal and returns answers that span multiple documents and entity hops. Use this when your content has strong entity relationships: legal documents, org charts, SOPs, process documentation, or any domain where how things relate to each other matters as much as what they are.

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How it works

  1. You connect your own Neo4j instance to Lyzr as a Data Connector.
  2. You create a Knowledge Base with Graph selected as the type and point it at that connector.
  3. You upload documents (PDF, DOCX, TXT, or Markdown). Lyzr parses each file to extract named entities and the semantic relationships between them.
  4. Entities are stored as nodes in Neo4j. Relationships are stored as typed, directional edges. The resulting graph is browsable in Neo4j’s native visual tools.
  5. Agents and API callers query the graph using natural language. Lyzr translates each query into a Cypher traversal and returns the relevant subgraph.

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Prerequisites

You must bring your own Neo4j instance. Lyzr does not provision one for you.
  1. Go to neo4j.com/cloud and sign up for a Neo4j Aura account.
  2. Create a database instance and copy the URI, Username, and Password from your Neo4j dashboard.
  3. In Lyzr Studio, go to Connections > Data Connectors, find the Neo4J GraphDB card, and add a new connection using those credentials.

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When to use Knowledge Graph vs. Classic Knowledge Base

NeedUse
Document Q&A, topic searchClassic Knowledge Base
Cross-document reasoning, entity relationshipsKnowledge Graph
Structured data, SQL-backed answersSemantic Model

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Next steps