You know this?

Many different application systems, each with its own database, many interfaces, enormous investments and yet an untamable parallel world with countless Excel files and "special applications". High complexity, complicated processes, redundancy, multiple maintenance and intransparency regarding the dependencies between different data fragments.

... and your wishes are commented again and again with "this is not possible!

This state of affairs is the result of a - for years (unfortunately) unchallenged - focus on processes and applications (applications) according to the principle "Every process has its own application"!

Once these applications are introduced, the accompanying complexity brings with it an attitude of no longer being able to grasp. 

However, processes cannot be frozen and the salvation of "best practice" standardization comes at the expense of much needed flexibility.

The focus should not be on processes, but on data and their relationships to one another.

Follow the paradima "data first - process second", because processes change, but data (models) form a stable foundation.

Build your own, company-specific data platform based on future-oriented graph technology and a robust methodology. Model and link your data fragments with each other, use small, role-specific micro-applications for their maintenance and you get ...

• more transparency
• better understanding of correlations
• higher acceptance
• clear data sovereignty
• simplified processes
• comprehensible change management

A fairly priced toolset and pre-configured modules with different focuses (e.g. image management, terminology management, parts lists, technical attributes, approval and contract management, requirements management and rule-based document generation) are assembled into "toolboxes", which are oriented towards the specific requirements of the subject areas PIM, PDM and SysLM.

With these tools we give you back the sovereignty over your data world. Transparency and traceability in the data are basic requirements to start with competence in discussions about AI, knowledge management and learning systems.