New Case Study
Reaching the Single Brain with Hume
‘The amount of savings in time and effort [the search optimization] can deliver for our home offices, for our customers, is incredible.’
--Mayank Gupta, SVP for data, LPL Financial
‘The amount of savings in time and effort [the search optimization] can deliver for our home offices, for our customers, is incredible.’
--Mayank Gupta, SVP for data, LPL Financial
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 graphs and Hume can help you detect and investigate money laundering activities.
‘The amount of savings in time and effort [the search optimization] can deliver for our home offices, for our customers, is incredible.’
--Mayank Gupta, SVP for data, LPL Financial
Fraud is becoming more and more complex. Learn how graphs and Hume can help you fight and detect fraud.
An introduction to Graph-Powered Machine Learning written by our very own Dr. Alessandro Negro. This book is an extraction of 60 combined years of experience in graphs, and explains how graphs and graph databases can serve machine learning projects.
GraphAware and Neo4j experts demonstrate how you can leverage knowledge graphs to help with compliance challenges.
‘GraphAware Hume and Neo4j have significantly reduced the amount of manual effort required to keep documentation consistent and mitigate compliance risk.’
Dr. Miro Marchi and Michal Trnka explore 10 of the most useful graph entity states using Cypher to enrich entities with contextual information enabling powerful interactions.