Euler Analytics Platform (EAP) uses an ontology as a data schema model because ontologies treat data in a way that makes relationships become visible. 

The ontologies of our platforms are based on the unique concept of Intelligence Objects (IO), developed by EULER Technology Solutions, making our platform much more relevant and accurate than generic Big Data engines.

The Intelligence Objects (IO) can be either business entities or technical entities.

Our platforms are fully configurable and customizable as per the organization’s business specificity. 

It integrates a centralized administration application to configure users profiles, roles, organization management, access rights management, as well as system reference tables.

EAP’s fully Euler Intelligence Fusion Center ted workflow engine allows the administrator to easily create and streamline existing business processes through the embedded workflow graphical designer, and to monitor tasks and alerts across the organization.

EAP is an ontology-driven platform based on the unique concept of IO Intelligence Object designed by EULER Technology Solutions, which makes our platform much more relevant and accurate than any generic big data engine.

An ontology is a form of knowledge management, it captures the knowledge within an organization as a model. It represents knowledge as a set of concepts within a domain and also captures the relationships between these concepts. This model can be queried by users to answer complex questions and display relationships across an enterprise, assisting in uncovering and finding hidden patterns and non-obvious relationships.

Another aspect of ontologies is that using ontologies for knowledge management is an alternative to source code. Traditional approaches capture knowledge and relationships established by different working groups as lines of source code. This approach while still popular is extremely hard to manage and can only be managed only by a small group of engineers who understand the code and cannot easily adapt to changes in the environment. Using ontology models rather than lines of code allows the system to be easily modified on-the-fly with the changing environments.

EAP Euler Analytics Platform stores the ingested data in a Hadoop type data lake. Hadoop is an open source framework for storage and large scale processing of data-sets on clusters of commodity hardware. 


Its scalability is almost unlimited and it only needs commodity based hardware to run on.


It can easily scale horizontally by adding additional compute and/or storage nodes, in order to accommodate petabytes of data.

Our solutions enable organizations of all sizes to gain analytical insights from large amounts of data through engaging exploratory analysis. You can visually explore all of your data with an easy-to-use, drag-and-drop interface without the need to subset or sample data. The solution helps you identify new patterns, trends and relationships in the data that were not evident before.
We know how important is data security to our clients, so we thought hard about this approach and devised a multi-dimensional security model that protects the integrity and confidentiality of the client data by using an access control mechanism defined around positions, roles and privileges.
With the increase in volume of the Data, it becomes very difficult to search or find what the user is looking for. EAP is equipped with a powerful search engine to display all the requested information, thanks to its indexing, querying, filtering and data search capabilities.
EAP Euler Analytics Platform is fitted with several Artificial Intelligence technologies to enhance automatic analytics capabilities, suggest relations, extract insights from unstructured data such as texts, social media, videos or audios…
EAP Euler Analytics Platform is fully designed to benefit from the Machine Learning capabilities to allow analysts to go beyond any limit by building their own complex machine learning algorithms for prediction or pattern recognition.