The business world is in a state of perpetual change. Spiraling amounts of data, new technologies, fluctuating market requirements, and the restructuring of existing value chains have a strong and significant impact. Unconventional, innovative market players are poised to offer better quality and faster service at a lower price, putting long-established market leaders under increasing pressure.

These intense processes of change mean that companies are facing tremendous challenges every single day. Speed and flexibility in process handling as well as more precise forecasts are crucial factors for success. Above all, information availability and data analysis are decisive factors, because that capability is what provides companies with the basis for making decisions based on a wide breadth of hard facts rather than relying on assumptions.


Linking data − extracting information − utilizing knowledge

According to a study by IDC, employees spend around 9.6 hours – that’s a whopping 24 percent of their working week − searching for relevant information.[1] That’s not surprising, considering the immense wealth of data and information produced by each individual department in a company every single day. This data, part of the entire body of corporate knowledge, is scattered throughout the various departments. Meeting the current demands of the market and the customer, however, makes it imperative that relevant, necessary, and contextual information is always available.

This is exactly where so-called insight engines come in. Behind this term, coined by the IT analysts at Gartner, lies an intelligent solution that makes it possible for information to be found in a way that is resource-efficient and to make that information available to the user in the right context for the respective business case.

In doing so, these systems use methods of artificial intelligence to capture and collect existing corporate knowledge, extract the information, and show correlations between the individual pieces of data in order to convey a comprehensive overall picture.

Using natural language processing (NLP) and natural language question answering (NLQA), search queries can be delivered in natural language and processed directly. These intelligent technologies can analyze and understand structured metadata as well as text content, and use this to correctly determine what the user needs. While NLP deals with human language, NLQA enables the linguistic interpretation of search queries. These technologies can identify the specific needs of the users and tailor the search results to perfectly correspond to them. The objective is to pinpoint the user’s needs and to match the search results in the respective context, so that instead of an endless list of search hits, the user only receives the results that actually correspond to the searched term − augmented by context-specific additional information generated by semantic analyses.

Other forms of artificial intelligence employed by insight engines include machine learning and deep learning. They provide the system with a kind of memory, meaning that the insight engine is capable of continuous learning. By constantly analyzing various work methods, such as how often or in which context certain information is pulled up, the technology learns the relevance of the individual pieces of data, prepares the data for the specific application case, the department, the user, and differentiates the facts accordingly to provide information in a way that is personalized and proactive.

For example, insight engine solutions enable the user to get a 360-degree view of all business-relevant data within the organization in response to a query. This comprehensive overview of customers, suppliers, responsibilities, and expertise is absolutely pivotal for success in the face of increasingly harsh competition.

Fig.1 - 360-degree view of all data
Fig.1 - 360-degree view of all data

Optimization of internal company time management

Businesses are still wasting valuable resources because their employees’ workflow is repeatedly interrupted while they search for the information they need − corporate data that is spread out across different parts of the company. Yet efficiency, speed, and flexibility are of paramount importance today. In order for companies to remain competitive, avoiding unnecessary overhead is crucial.

Intelligent solutions such as insight engines are an effective tool for optimizing internal company time management. Information can be retrieved easily without switching over to the core IT system (where the data is stored). With the preview function (data is retrieved from a generated index), the results can be rapidly searched and pre-filtered. This allows users to access the information they need more quickly. All data is processed clearly and coherently, making it ideal for further processing. The user automatically switches to the required application only when interacting with the search hit. This simple information retrieval is also available using a mobile search function, which makes every day work a lot easier for field staff. The intelligent solutions allow access to the entire knowledge base across all mobile devices from anywhere at any time. Information retrieval is still possible even if the related applications are not installed, since here again, the preview function provides access to the contents.


Rapid Integration

Insight engines are high-end products with an out-of-the-box character. They can be easily implemented in the company without the need for an expensive and time-consuming implementation project. Using connectors for the different data sources such as network drives, SAP, Microsoft SharePoint and numerous ECM systems, all company data can be easily and efficiently integrated into the company. These intelligent systems offer an effective solution for big and small companies from a wide range of industries.

Fig.2 - Rapid integration in the company
Fig.2 - Rapid integration in the company

Wide-ranging applications, but security comes first

Insight engines can be used in a variety of departments, disciplines, and business units. The preparation and presentation of the data is tailored precisely to the requirements of each user’s role and position in the company. Thus, the insight engine can provide support despite the diverse challenges and needs of each different department, employee, and application case.

Although these intelligent systems enable rapid and uncomplicated access to company data, the issue of security is the top priority. For each search query, the insight engine checks the access authorization, which is stored directly at the data sources. In this way, every employee receives a specific, individual view of the company’s knowledge, and even short-term changes in position or department are immediately taken into account.


Additional application possibilities

Insight engines have even more features. For example, they can be used for the automated classification of documents, because they have the ability to analyze, interpret, and forward the contents of documents to the appropriate department. Here again, this ability is based on a form of artificial intelligence. Using machine learning and deep learning, patterns and text combinations can be defined in advance to serve as the basis for classifying the documents.

As a self-learning system, the insight engine is continually expanding its existing knowledge, using past experience to correctly categorize the various documents and forward them accordingly.

Fig3 - Data extraction from documents for classification
Fig3 - Data extraction from documents for classification

This feature is particularly useful in companies with large amounts of incoming mail such as the customer service departments for insurance companies, banks, and the like.

Since communication channels have become more diverse in recent years, employees have to struggle daily with a flood of incoming mail arriving at the company in various formats and via social media, e-mail, and other channels in addition to traditional mail. This makes classification and distribution to the various relevant departments and employees increasingly difficult and time-intensive. Insight engines can help accelerate these processes and make things easier for employees.



The digital transformation involves a profound change in the usual company processes, procedures and working methods, and has had far-reaching effects on the business world.

Intelligent solutions such as insight engines provide a solid foundation to advance digital transformation within an enterprise. An insight engine’s technology makes it possible to find, extract, analyze, and interpret information as quickly as possible. The data is processed, linked, correlations identified, and then consolidated into a comprehensive view in the right context. This extensive cross-linking of applications and departments ensures that the company’s knowledge is provided quickly, completely, smoothly, and in an intuitive and personalized manner.

This way, business processes and workflows can be reorganized, creating real competitive advantages.


[1] Feldman, S; J. Duhl, J. R. Marietta und A. Crawford (2005): The Hidden Costs of Information Work, IDC White Paper 2005

About the author: Kathrin Stadler is a knowledge manager at Mindbreeze GmbH. As a trend scout, she is always on the lookout for the most cutting-edge innovations and developments in the areas of enterprise search, applied artificial intelligence, and big data.

Mindbreeze GmbH is a provider of appliances and cloud services. The Mindbreeze insight engine understands information and provides a consolidated view of corporate knowledge, regardless of where (data sources) and how (structured, unstructured) the data is stored.

Pictures: Mindbreeze GmbH, author picture: via xing

Katrin Stadler
Katrin Stadler