Information manipulation and how to defend against it is a critical dimension of operating in today’s information landscape. Whether it be misinformation (incorrect or misleading information) or disinformation (deliberately deceptive information) through impersonation, deepfakes of various kinds, fake content sites and so on, the problem is massive and growing.
Experts agree that the threat is significant. The World Economic Forum, for example, ranks the spread of misinformation and fake news as one of the world’s top global risks. Additionally, University of Baltimore Professor and Information Systems expert, Roberto Cavazos, conducted a commissioned study entitled Introduction to the Economic Cost of Bad Actors on the Internet to quantify the size of this problem, primarily in terms of economic impact, in order to truly understand the full scale of “internet harm” as he terms it. The stated goals of the study include “To measure the global economic price paid by businesses and society due to problems including ad fraud, online bullying, and fake news… in the form of both direct and indirect costs.” Cavazos’ conservatively tallied the total direct costs alone at $78 billion, just by 2019. That includes nearly $10 billion annually in brand equity and reputation management costs. To make matters even more challenging, the technology options available to combat this issue have not kept pace with the problem, so organizations are left wondering how to protect themselves.
In creating the Information Defense System, Limbik’s goal was to take their deep domain expertise in security and information assessment, as well as reputation management, and build that into a scalable Artificial Intelligence (AI) platform. The current solutions simply identify threats, but Limbik employs
cutting-edge AI to predict threats and recommend response options. By combining their domain expertise and IP, together with graph-database technologies and graph data science techniques, including powerful new techniques in machine learning, Limbik is moving far beyond the inadequate technology options available today—with a solution that can scale for their customers as threats evolve.
Paramount to deploying their predictive analytics, Limbik needed to create a managed information pipeline of structured and unstructured data that also remained scalable. To accomplish this, Limbik turned to the Graphable team in what has led to a strong partnership around both Hume and Neo4j.
By combining the capabilities of the industry-leading Neo4j graph database, and the cutting-edge Hume platform for graph ETL and analytics, with Graphable’s unique skills around graph-centered data pipelines and graph data science, Limbik found the perfect fit for their unique requirements for highly connected graph capabilities, ETL, and analysis.
In particular Hume Orchestra, a scalable, graph-centric information pipeline management capability for both structured and unstructured data is a pivotal element of the solution. With so many sources, across many different types of incoming data, at high volumes and with the unique Neo4j graph database target, it had to be managed well and at scale by a purpose-built capability only found in the Hume platform.
The Graphable data and graph data science consultant teams initially worked with Limbik experts to craft the optimal approach using Neo4j and Hume in concert. Once in place, the Limbik team successfully took ownership to continue expanding and evolving the solution. This process highlights what has become a productive partnership, bringing together Limbik’s deep domain and technical expertise with Graphable’s expertise related to graph database and graph data science.
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Graphable delivers insightful graph database (e.g. Neo4j consulting) / machine learning (ml) / natural language processing (nlp) projects as well as graph and Domo consulting for BI/analytics, with measurable impact. We are known for operating ethically, communicating well, and delivering on-time. With hundreds of successful projects across most industries, we thrive in the most challenging data integration and data science contexts, driving analytics success.
Still learning? Check out a few of our introductory articles to learn more:
- What is a Graph Database?
- What is Neo4j (Graph Database)?
- What Is Domo (Analytics)?
- What is Hume (GraphAware)?
We would also be happy to learn more about your current project and share how we might be able to help. Schedule a consultation with us today. We can discuss Neo4j pricing or Domo pricing, or any other topic. We look forward to speaking with you!