Trusted Data Processing Across Company Boundaries with KnowledgeX

Building innovative solutions

Marcel Muller
Marcel Muller, Founder of KnowledgeX

Dr. Marcel Müller is a German researcher and entrepreneur. Marcel received his Ph.D. in Computer Science on the Topic of Trust-aware Business Processes with Distributed Ledger Technologies from TU Berlin. Before starting KnowledgeX, Marcel has been working on different other projects. He has industry experience (Deutsche Telekom, Siemens) and a wide research experience (TU Berlin, Fraunhofer CESE, Universidade de Lisboa) in the fields of blockchain and data science. Additionally, to his work at KnowledgeX, Marcel is an expert at the Center for Deep Tech Innovation (

KnowledgeX analyses and processes data-driven decisions in a fully trusted, traceable and transparent environment

In recent years, data-driven solutions have become essential for businesses that want to create value. For instance, energy companies can use their operational data to reduce their CO2 emissions; logistics firms can employ intelligent analytics and optimisation techniques to expedite the supply chain process; and healthcare providers are better equipped with prognostics based on big data analysis in order to improve patients’ lives.
Yet, this data is highly private and sensitive and must be secured to protect the customers’ interests. This is where privacy-preserving technologies come in. Privacy-preserving technologies use cryptographic techniques to ensure that data remains private while still allowing it to be used for analytical purposes. These methods can help businesses to secure their data and prevent unauthorised access or manipulation of information, as well as protect their customers’ privacy.

KnowledgeX is a platform for privacy-preserving cross-company data processing. By using blockchain technologies and trusted computing, we let users define where and how their data can be processed and by which actors. We create a shared audit trail that lets users at any point in time see what happened.

The Solution: Shared problem solving based on confidential data

KnowledgeX consists of two parts: the data science marketplace and a trustworthy data science computation environment.

The KnowledgeX marketplace connects data scientists and data owners. Data owners can create data science gigs and specify which specialized skills they need for the gig. For example, a water infrastructure operator needs a specialist in time series analysis and anomaly detection to predict which of the water pipes are most worn out and likely to burst. KnowledgeX selects the three best-suited candidates for the gig and lets the data owner decide which one to choose.

The KnowledgeX confidential computing environment leverages the iExec platform to let the data owner have full control over their data. Data owners can decide where their data is being processed. They can also decide what a data scientist can do with the data in general. KnowledgeX and iExec let data owners audit what happened with their data afterward. This builds trust that in current platforms does not exist.

How is KnowledgeX contributing to the ONTOCHAIN software ecosystem?

Within NGI ONOTCHAIN, we explored the first use case: a privacy-preserving marketplace that lets companies find specialised data scientists for their specific use cases in a marketplace and enables traceable and transparent knowledge generation with trusted execution environments and blockchain technologies. We developed a concept for data-driven collaborations through federated analytics, a privacy-preserving marketplace, and the required tools and frameworks to enable companies to create value with their data collaboratively.

By using knowledge, companies can trust that their data is secure and private while still allowing it to be used for analytical purposes. We are proud to be part of this paradigm shift, which will usher in a new era of data-driven collaboration. We are excited to continue exploring the potential of privacy-preserving technologies and empowering businesses of all sizes with secure access to their data.

The NGI support helped us to create the first use case and validate it quickly.

Continuity after NGI ONTOCHAIN

After ONTOCHAIN, we explored that there are many other use cases where the general problem of privacy-preserving inter-organisational data processing also exists. The problem is much bigger than just a data science marketplace. In our current projects, we are looking into privacy-preserving employee data processing, intra-company collaborations and many other use cases.

KnowledgeX can help in any use case where:

  • Multiple parties need to collaborate on data
  • The parties only trust each other to a limited extent
  • There must be an audit trail for data

For further information, if you want to know more about KnowledgeX, please check out our resources (

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