mailitics

Category: Neo4j

  • GliNER2: Extracting Structured Information from Text

    GliNER2: Extracting Structured Information from Text From unstructured text to structured Knowledge Graphs The post GliNER2: Extracting Structured Information from Text appeared first on Towards Data Science. Tomaz Bratanic Go to original source

  • How To Build a Graph-Based Recommendation Engine Using EDG and Neo4j

    How To Build a Graph-Based Recommendation Engine Using EDG and Neo4j Use a shared taxonomy to connect RDF and property graphs—and power smarter recommendations with inferencing The post How To Build a Graph-Based Recommendation Engine Using EDG and Neo4j appeared first on Towards Data Science. Steve Hedden Go to original source

  • Using Claude Skills with Neo4j

    Using Claude Skills with Neo4j A hands-on exploration of Claude Skills and their potential applications in Neo4j The post Using Claude Skills with Neo4j appeared first on Towards Data Science. Tomaz Bratanic Go to original source

  • Implementing DRIFT Search with Neo4j and LlamaIndex

    Implementing DRIFT Search with Neo4j and LlamaIndex Combining global and local search to get the most accurate response The post Implementing DRIFT Search with Neo4j and LlamaIndex appeared first on Towards Data Science. Tomaz Bratanic Go to original source

  • Preventing Context Overload: Controlled Neo4j MCP Cypher Responses for LLMs

    Preventing Context Overload: Controlled Neo4j MCP Cypher Responses for LLMs How timeouts, truncation, and result sanitization keep Cypher outputs LLM-ready The post Preventing Context Overload: Controlled Neo4j MCP Cypher Responses for LLMs appeared first on Towards Data Science. Tomaz Bratanic Go to original source

  • How to Evaluate Graph Retrieval in MCP Agentic Systems

    How to Evaluate Graph Retrieval in MCP Agentic Systems A framework for measuring retrieval quality in Model Context Protocol agents. The post How to Evaluate Graph Retrieval in MCP Agentic Systems appeared first on Towards Data Science. Tomaz Bratanic Go to original source

  • GraphRAG in Action: A Simple Agent for Know-Your-Customer Investigations

    GraphRAG in Action: A Simple Agent for Know-Your-Customer Investigations This blog post provides a hands-on guide for AI engineers and developers on how to build an initial KYC agent prototype with the OpenAI Agents SDK. We’ll explore how to equip our agent with a suite of tools (including MCP Server tools) to uncover and investigate potential…

  • Agentic GraphRAG for Commercial Contracts

    Agentic GraphRAG for Commercial Contracts In every business, legal contracts are foundational documents that define the relationships, obligations, and responsibilities between parties. Whether it’s a partnership agreement, an NDA, or a supplier contract, these documents often contain critical information that drives decision-making, risk management, and compliance. However, navigating and extracting insights from these contracts can…