With our solution, you will gain new insight across disciplines and information silos without moving data. See information from any system in contexts across activity types, departments, customer segments and geography.

The IntOp solutions helps you find the patterns in your information without building new information silos, changing existing workflows or train users on new technology. Reduce risk, avoid errors and reduce effort in handling and analyzing large amounts of data.

IntOp Engine operationalizes data by digitizing it and gathering it into numerous contexts. The contexts are designed either generically for the business type or segment, or specifically for the needs of user groups based on the information they have available or the processes they work by.

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:

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IntOp Engine has flexible connectors that connect to data sources and automates data harvest. Content of files or records and all metadata on the source and in the file are harvested. During implementation of the solution, all data and metadata will be harvested. Thereafter, an ongoing incremental load will be run periodically to harvest changes. As IntOp Engine is connected to Active Directory and the access policies of the sources, identity and access rights are also harvested alongside the data.

IntOp Engine is set up on premises or in cloud, depending on what is most efficient regarding security and data ingestion. The IntOp Connector is then connected to some or all the sources where data within scope is stored. The most common file repositories, like Fileserver and SharePoint are often the starting point. These are the source where most data are stored, and where the complexity and is highest. During and after data harvesting, statistics regarding the harvested data will be made available. For editable files, all data and metadata may be ingested by default, or only metadata. For non-editable files, all data and metadata may also be ingested, but content harvest (OCR) is dependent on the quality of the files. All raw data and metadata are stored in a data store for use by the IntOp data pipeline.

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The main differentiator of for IntOp Engine is the IntOp Context Layer. This is IntOp’s patent pending technology to add context 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; a problem, department.

During or before the initial data harvest, Contexts for use in sorting the data is designed and implemented in the Context Layer. Existing contexts offered in the standard set-up may be enough, or a simple context that makes it possible to sort data based on high level categories for the organization could be added. For the following use, additional contexts may be added as the need arises, and existing or new contexts may be edited, improved or changed. The initial design of the contexts will be done by IntOp and the customer in cooperation. Further management of the contexts may be done by both client personnel and IntOp. No IT experience or developer skills are needed to design og manage the contexts in the IntOp Context Management Tool. As the needs of the organization develops, the IntOp Context Layer may be changed accordingly, so it continues to adapt to new scenarios, user stories or business cases.

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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 such as Filetype, Extension type, Source, Author and Date.

Any combination of filters will result in a data selection. This selection may be saved, shared and re-used. When one user saves and shares a selection, the resulting link will open the same selection for the users that receives it, while keeping the access rights intact, showing only the files each user has access to in the sources. As a selection is dynamic, the number and types of files will change as more data is ingested, or the Context Layer is changed and improved.

Thanks to a powerful API, data from the IntOp Engine may be navigated or displayed in both IntOp Fetch, IntOp Fetch for 3D, IntOp Fetch for GIS. In addition, statistics may be made available in BI dashboards for further insights and analysis.

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