Over 10,000 physical typewritten documents from 1932 to 1941 had to be digitised, structured, and connected in order to create a single, centralised source of knowledge, for enabling the analysis of historical processes.
Dive deeper into Hume Orchestra, our data-driven orchestration tool, with our CTO, Christophe Willemsen.
Graphs are commonplace in investigative, intelligence, and law enforcement work. One of the primary advantages of a graph is to connect data from various data sources, digital and human, and maximize insights across deep and complex networks of connections, bringing them together in fusion centers for a centralized view of suspicious activities. For analysts, data quality and trust is key. The reliability, validity, and general consistency of data sources that contribute to forming real world fused entities is a factor that influences the analysts’ interpretation of events. This session talks about the challenges related to surfacing these aspects of data provenance and various approaches that can be employed to address them using Neo4j. We will touch on graph modeling, implications for data security, and how sources and information ratings can be effectively shared with analysts who need access to them.
Learn how graphs and Hume can help you tackle logistics challenges.
Learn how Hume, graph analytics and machine learning can be powerful tools to help you detect, investigate and prevent money laundering activities.
Fraud is becoming more and more complex. Learn how graphs and Hume can help you fight and detect fraud.
GraphAware and Neo4j experts demonstrate how you can leverage knowledge graphs to help with compliance challenges.
In this video, Michal Bachman, CEO of GraphAware, discusses how graph data can be used to identify unknown unknowns in intelligence. He emphasizes the importance of context in gaining a deeper understanding of complex systems and how graph data can reveal patterns, relationships, and connections that were previously unknown. Overall, the video provides valuable insights into the potential applications of graph data in intelligence.