The IntOp solution is a patent-pending SaaS solution that offers AI-capabilities that enables organizations to structure large volumes of unstructured data across all sources by sorting it in patterns called Contexts. The data is then presented in intuitive filters for end-users, management and analysts.

IntOp Engine also generates statistics about the contextualized information that is served to the users through BI Dashboards. The solution consists of the IntOp Engine, IntOp Context Layer and the information discovery tool IntOp Fetch

The Harvest-Prepare-Present process that IntOp’s technology enables, explained:

1-HARVEST IntOp Engine has flexible Connectors, connecting the data sources and automating data harvest. Content of files or records and all metadata on the source and in the file are harvested. Thereafter, it will periodically harvest changes. As IntOp Engine is connected to Active Directory and the access policies are also harvested alongside the data.

IntOp Engine is set up in Azure completely, or as a hybrid solution where data harvest is done on premise, depending on what is most efficient regarding security and data ingestion. Common file repositories, like Fileserver and SharePoint are often the starting points. These are the source where most data are stored, and where the complexity is highest.

2-PREPARE The main differentiator of IntOp Engine is the IntOp Context Layer. This is IntOp’s patent pending technology to offer AI capabilities without the effort and knowledge of data scientists and developers. The Context Layer adds contex to data. Context may be added to perform information inventory, gain insights, sort data or as fit for purpose data navigation choices for user groups. The Context Layer receives language-based instructions about the contexts. This means that anyone that knows how to describe the context, will know how to implement it. No IT experience or developer skills are needed to design or manage the contexts in the IntOp Context Management Tool. As the needs of the organization develop, the IntOp Context Layer may be changed accordingly, so it continues to adapt to new scenarios, user stories or business cases.

3 - PRESENT For the analysis of data, IntOp will by default make all data available in IntOp Fetch. Analysts, employees, and management may navigate, collaborate, discover and filter data in Fetch using the filters based on the defined contexts in the IntOp Context Layer and appropriate facets. Any combination of filters will result in a data selection. This selection may be saved, shared and re-used.