See how GenAI + graph algorithms enable AI agents to reason, learn, and uncover insights—beyond static data or simple retrieva

This session presents the knowledge graph as a dynamic reasoning engine, not just a static data repository. Learn how to deploy autonomous AI agents that intelligently navigate the relationships within your connected data to discover profound insights. Leveraging GenAI and graph algorithms, this agentic approach moves beyond simple retrieval to create a verifiable foundation for AI systems that can reason and learn.

See how GenAI + graph algorithms enable AI agents to reason, learn, and uncover insights—beyond static data or simple retrieva

This session presents the knowledge graph as a dynamic reasoning engine, not just a static data repository. Learn how to deploy autonomous AI agents that intelligently navigate the relationships within your connected data to discover profound insights. Leveraging GenAI and graph algorithms, this agentic approach moves beyond simple retrieval to create a verifiable foundation for AI systems that can reason and learn.

Join our session on GraphRAG, blending graph theory and generative AI for intuitive, enriched data interaction and smarter insights.

From a data perspective, an ideal scenario is one where practitioners can have a meaningful conversation with their data. In an era where data is both abundant and critical, the need for innovative methods to interact with and understand complex datasets has never been greater. Enter GraphRAG (Graph-based Retrieval-Augmented Generation), a cutting-edge approach that revolutionizes data interaction by seamlessly integrating graph theory with generative AI.

GraphRAG leverages the power of a knowledge graph to represent relationships within data, enabling more intuitive navigation and retrieval of relevant information. By augmenting these capabilities with state-of-the-art generation models, GraphRAG provides users with enriched, context-aware outputs that significantly surpass traditional query-response systems.

Attendees will gain insights into the underlying principles of GraphRAG, its architectural components, and practical applications across various domains, from healthcare to finance. We will demonstrate real-world use cases, showcasing how GraphRAG not only improves efficiency and accuracy in data handling but also democratizes access to complex insights, empowering users to reach their ideal state of conversing with their data. Join us to discover how GraphRAG is paving the way for the future of intelligent data interaction.

From a data perspective, an ideal scenario is one where practitioners can have a meaningful conversation with their data. In an era where data is both abundant and critical, the need for innovative methods to interact with and understand complex datasets has never been greater. Enter GraphRAG (Graph-based Retrieval-Augmented Generation), a cutting-edge approach that revolutionizes data interaction by seamlessly integrating graph theory with generative AI.

GraphRAG leverages the power of a knowledge graph to represent relationships within data, enabling more intuitive navigation and retrieval of relevant information. By augmenting these capabilities with state-of-the-art generation models, GraphRAG provides users with enriched, context-aware outputs that significantly surpass traditional query-response systems.

Attendees will gain insights into the underlying principles of GraphRAG, its architectural components, and practical applications across various domains, from healthcare to finance. We will demonstrate real-world use cases, showcasing how GraphRAG not only improves efficiency and accuracy in data handling but also democratizes access to complex insights, empowering users to reach their ideal state of conversing with their data. Join us to discover how GraphRAG is paving the way for the future of intelligent data interaction.

Join our session on GraphRAG, blending graph theory and generative AI for intuitive, enriched data interaction and smarter insights.