Audit – in many companies, this announcement causes beads of sweat on the employees’ foreheads. Not because it can go badly but because the preparation for it is incredibly time-consuming. Do we have all the information we need? Or are we missing important data? Classical systems can only deliver what we look for. Conversely, this means that the question determines the results. But how are you supposed to do elaborate research and data preparation in addition to your daily work? You don’t! Because knowledge mining can do it.
Here, artificial intelligence supports searches in all possible data pools and delivers relevant content. And not only for audits, but also if, for example, contract terms or customer support efficiency needs to be checked.
Thanks to knowledge mining, you can always see the current state of knowledge in your company. And can, thus, start making improvements in the right places.
Knowledge mining involves the use of several AI tools, such as Azure Cognitive Services. They search content from various sources for patterns and matches, and then curate them. This means that employees no longer have to search through masses of unsorted data.
The highlight: the validity and reliability of automatic searches are particularly high.
AI directly makes sense of the content found, weights it, and ignores nonsensical hits. Thus, it is possible to continue working directly with the information.
Since AI does not search “blindly” but learns continuously, knowledge mining provides relevant information. No more jumble of marginal information, repetitions, and random hits, which has, up to now, made the processing so time-consuming.
Searching and sorting content is one of the most time-consuming tasks. If special tasks such as audits are added, the burden is multiplied. Knowledge mining provides real relief here and gives employees more room to devote themselves to their actual tasks.
Knowledge mining is a sub-discipline of artificial intelligence (AI). Intelligent services are combined in such a way that knowledge can be quickly extracted from vast amounts of data. Organizations can then use information more easily and better recognize relationships and patterns within their structures.
Artificial intelligence (AI) has two major advantages over classical data mining systems: it does not search “blindly” or within rigid guidelines but is constantly learning. This increases the validity and reliability of the results (clarity of results). Knowledge mining also groups the knowledge in such a way that it can be worked with directly. On the one hand, this relieves the burden on employees and, on the other, allows deep insights into your own company.
Knowledge mining takes place in three steps:
Our core is the development of artificial intelligence. To this end, our experts repeatedly collaborate with university researchers. The German Federal Ministry of Education and Research (BMBF) is funding two of our current research projects on improving work processes through AI.
In order for artificial intelligence to bring sustainable added value, AI knowledge is also needed in the companies themselves. With our AI Academy, we, therefore, help you to build an internal competence team.
With our colleagues as well as with our business partners and customers. Thanks to our strong staff retention, we can ensure that you benefit from long-term support from the same contact persons. This has a positive effect on the quality of our services and on our whole business relationship.
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