AllegroGraph in Action: Layered AI and Knowledge Graphs

Watch a 25-minute demonstration showcasing how AllegroGraph combines vector search, LLMs, reasoning, and graph queries into a unified, layered AI system for deep insights across cybersecurity, finance, and healthcare. Franz Inc. CEO Jans Aasman demonstrates how AllegroGraph powers semantic search, vector embeddings, Retrieval-Augmented Generation (RAG), and Graph RAG to connect structured and unstructured data for actionable intelligence. Observe real-time examples of extracting intelligence from 120,000+ literal-rich data elements, using vector search for semantic matching of cybersecurity threats, querying with natural language instead of SPARQL, and integrating STIX, MITRE ATT&CK, NIST, and enterprise-specific data. See how analysts can ask questions like "Who is affected by Log4j?" or "What are the main bad actors in China attacking financial institutions?" and receive accurate, explainable results without writing code. The demonstration culminates by showing AllegroGraph's layered AI processes—SHACL constraints, vector embeddings, prior query examples, and large language models—answering complex questions entirely through natural language, making advanced cyber analysis accessible to non-technical users.