Every large corporation nowadays suffers from too many poorly interconnected IT systems, databases, and platforms.

Even from the end-user perspective, this situation is quite stressful and energy-consuming. But if we look at it holistically, we’ll see large business performances considerably impacted by these dozens or even hundreds of platforms and systems with their respective databases.

Lack of interoperability is the most apparent issue. Still, there is another one behind it: data silos, multiple copies of similar data without clear understanding which version is the most recent.

This data silos automatically implies that there is no control over data quality and that your technical teams spend lots of effort to interconnect all these often almost incompatible systems and to coordinate their incoherent ontologies. Last but not least, it negatively affects data transmission outside the company, including both communications with its clients and all interactions with its suppliers and contractors.

All these issues constantly keep too many human resources busy, consume too much energy, and result in underperformance of the whole business

The aforementioned problems have been a headache for a few generations of system administrators and software engineers. Hundreds of “quick API integration” startups and millions lines of custom code later, perfect compatibility of multiple applications and databases is still a dream: links amongst them remain unstable, every change in each of them might require some adjustments in APIs, scripts, other databases, etc.

Basically, despite all these continuous efforts (including international initiatives and standards, such as IDS or Gaia-X), different systems – especially when there are hundreds of them – don’t really understand each other, and the case seems to be hopeless.

It is hopeless because an interconnection (even with a standard API like IDS suggests) may help to solve only one issue: it will open information flow from one system to another. But it will not even try to resolve the remaining problems:

• Data silos
• Vendor lock-in leading to lower systems efficiency
• Multiple user accounts, one per system used

And yet we believe that the ultimate solution exists. Instead of connecting platforms with APIs our Web 3.0 Data Space architecture allows every software system to interact with the same original data, stored separately for every subject or object (and not for each software system).

Corporate data doesn’t have to fit Procrustean beds of a multitude of different databases. Instead, it can be stored in a universal and fully machine-readable Linked Data format on separate secure virtual servers – we call them PODs – for each object you interact with. Each machine or piece of equipment you use, each client or contractor you are connected with, can have such a POD with every single piece of data related to them stored there.

Our Web 3.0 Data Space approach brings enterprise IT systems to the new era by transforming the very way people and machines interact with data.

Things impossible yesterday despite all the IoT development, now become real through our solutions: 

• While buying any piece of equipment, you automatically receive its digital twin on its POD, which instantly integrates with your current systems and starts providing data for all your models, estimates, and predictions
• The same piece of equipment controls its own wear and notifies the service team (even outside of your company) exactly when they are needed for maintenance and repair of its components
• The infamous fake parts issue isn’t an issue anymore: such parts can be detected and even reported to the original manufacturer with no human intervention
• At last, every machine or device can be rated by their owners based on a number of criteria, and these rating will directly influence the reputation (we call it e-Karma) of their respective manufacturers
• And many more equally wonderful effects