Knowledge Graph

Lyzr Studio’s Knowledge Graph empowers you to transform unstructured documents into deeply connected semantic networks — enabling advanced reasoning and multi-hop question answering. This is ideal when your domain requires relationship-based understanding beyond simple retrieval.

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1. Choose Knowledge Base Type

Start by selecting Knowledge Graph as the type when creating a new Knowledge Base. This will activate Lyzr’s graph-building and Neo4J integration features.

Knowledge Graphs are ideal for content where relationships between concepts, people, tools, or processes are important (e.g., legal documents, SOPs, or technical documentation).

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2. Prerequisite: Set Up a Neo4J Account

Before using the Knowledge Graph feature, you must configure a Neo4J database instance. Follow these steps:

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Create a Neo4J Aura Account (Cloud)

1. Visit https://neo4j.com/cloud and sign up for a Neo4J Aura free or paid account.
2. Create a new project and launch a free-tier database.
3. Once created, copy the following credentials from your Neo4J dashboard:
   • URI (e.g., neo4j+s://yourdb.neo4j.io)
   • Username
   • Password
4. You can test the connection directly inside the Neo4J Console to ensure it works.

Tip: Use the free tier during development. Upgrade only when you scale.

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3. Configure Neo4J in Lyzr

Once your Neo4J instance is ready:

1. Go to Studio > Data Connectors.
2. Click Create New.
3. Select Neo4J from the list of database types.
4. Enter:
   • Name (e.g., “My Knowledge Graph DB”)
   • URI, Username, and Password from your Neo4J account.

Lyzr will now be able to construct and manage a graph-based semantic layer using this connection.

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4. Upload and Parse Documents

Next, upload your documents or text files. Supported formats include:

• PDF, DOCX, TXT, Markdown
• Multiple files can be uploaded at once

Lyzr will automatically:

• Parse content using intelligent NLP techniques
• Identify entities and their types
• Extract semantic relationships (e.g., “Person A manages Team B”, “Tool X is used for Task Y”)

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5. Graph Construction and Storage

Using the parsed content and connected Neo4J backend:

• Entities become nodes in the graph (e.g., people, tools, organizations).
• Relationships are modeled as typed edges with directionality.
• The resulting graph is stored in Neo4J and visualizable through native tools.

This structure enables complex reasoning and dynamic query resolution.

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6. Query the Knowledge Graph

Once built, your KB can be queried via agents or directly from Studio.

• Use natural language (e.g., “Which tools are used in the product launch process?”).
• Lyzr translates queries into graph traversals using Cypher (Neo4J query language).
• Results can span across multiple documents and entities.

Compared to traditional RAG, this method ensures higher accuracy and semantic depth.

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Summary

The Knowledge Graph KB elevates your AI agents from basic retrieval to knowledge reasoning — making them capable of navigating context-rich, connected data spaces effortlessly.