How it Works


What is the Future of EQ Knowledge graph?

Before, mapping of valuable intelligence data between systems often resulted in reduced information accuracy due to inflexible schema mapping and format constraints on data ingestion. The EQ Knowledge Graph provides a completely dynamic and flexible ontology that can rapidly evolve to meet the needs of field intelligence analysts and operators.
The EQ Knowledge Graph is designed to improve the discovery and obtainment of intelligence information to circulate and produce intelligence fused outputs, creating an environment where intelligence fused outputs, creating an environment where intelligence systems can communicate. The logical architecture defines the components of the EQ Knowledge Graph and how they work together to provide the services that the Equitus platform uses.



The EQ Knowledge Graph consists of several data processing pipelines allowing for seamless ingestion, transformation, querying, storing, and analysis of data from any source, in any format. Each data source can be a system, application, or repository that you might want to retain in your organization.


The EQ Knowledge Graph is designed to cater to a wide range of use cases and skill levels. The system is built with a variety of entry points, spanning experience ranging from first-time analysts to professional data scientists.


A core focus of the EQ Knowledge Graph is the ability to integrate Equitus with legacy systems non-intrusively, leaving legacy applications and data untouched for continued usage. With a particular emphasis on legacy databases, it is straightforward to shift infrastructural elements of your current architecture to the ODF without upsetting user's workflows.

Logical Architecture


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