Accessibility Tools

  • Content scaling 100%
  • Font size 100%
  • Line height 100%
  • Letter spacing 100%


Making the entire knowledge of employees available, using it beneficially and expanding it: A process that often involves high manual effort and that is inefficient. With msg.ProfileMap, companies can use an AI-based procedure to collect their knowledge and to implement a machine-based knowledge representation.

AI-driven skill and competence management

Nowadays, companies in all industries are more dependent than ever on making the best use of their employees' expertise. This is especially true for know-how in areas such as technology, business processes, strategy and methodology. This "human capital" must be aligned in the best possible way with the requirements of the company and its customers as well as with market trends.

The challenge

The means by which companies currently try to match the skills of their employees with the requirements of customers and the market are characterized by high manual processes and heterogeneous data sources. 

One way to solve this problem is an approach that uses methods from artificial intelligence to collect the knowledge of a company and to convert it into a machine-based knowledge representation. An AI-instance as a  learning system uses this knowledge to perform a cognitive analysis of text collections and to identify connections (knowledge discovery) using technologies such as Natural Language Processing (NLP) and neural networks. 

The solution

One solution based on this approach is ProfileMap from msg. msg.ProfileMap draws on a process called Named Entity Recognition (NER). NER analyzes texts that are based on natural language and whose information content is therefore available in semi-structured or unstructured form. 

The special feature of this cognitive text analysis is that it collects all information related to an issue and creates a relationship between the information provided. The result is a knowledge graph. It maps the complex relationships between entities, topics and fields of competence and makes them accessible for analysis. msg.ProfileMap is capable of determining such contextual relationships between data and to visualize them. 

This structure can now be used for various use cases. This includes in particular a AI-based search and matching of persons to project requests. Using a machine learning model, msg.ProfileMap matches the request text with the profiles of potential candidates. For this purpose, msg.ProfileMap uses not only the explicitly specified information, but also the information that can be derived from the knowledge graph. 

Using these AI technologies, staffing processes can be accelerated sustainably, transparency about the future viability of the company and the workforce can be shown and development paths for all employees can be identified.

Find quickly instead of searching for a long time – Benefits of msg.ProfileMap

  • Find suitable employees quickly and easily using Natural Language Processing (NLP) 
  • Flexible and balancing staffing 
  • Avoid overbooking of scarce resources 
  • Identify bottlenecks in time and take countermeasures 
  • Expand the competence potential of employees 
  • Increase competitiveness of your company 
Msg Profilemap Overhead 20200616

Would you like to learn more about the diverse application areas?

Get in touch

Invalid Input

Stefan Walter 200x200

Stefan Walter
Division Manager
HCM - Competence Management

+49 172 4632842