Overview
This solution represents a novel innovation as it automates data handling processes, enhances scalability across multiple industrial domains, and enables privacy-preserving collaboration among distributed partners within eccenca‘s product Corporate Memory (CMEM). The asset consists of an IT solution designed to enable intelligent data pipelines and advanced data integration methods that support large-scale machine learning through federated learning approaches.
Our result
The solution enables intelligent data pipelines and advanced data integration methods supporting large-scale machine learning through federated learning approaches. It automates data handling, improves scalability across industrial domains, and enables privacy-preserving collaboration among distributed partners. Within CLEVER, eccenca supported partners in implementing data pipelines, modelling distributed data sources, and applying standards for data integration. The results will be further developed and integrated into eccenca’s commercial product, Corporate Memory (CMEM).
Needs and target audiences
We engage senior enterprise decision makers and Heads of Data, AI, and Digital Transformation in large organisations across regulated sectors including critical infrastructure, energy, manufacturing, logistics, defence, and pharmaceuticals. We also seek partnerships with global system integrators and consulting firms needing sovereign, explainable AI and data platforms for scalable deployment. In addition, we target public-sector stakeholders and regulators focused on digital sovereignty, trustworthy AI, and resilient data infrastructures aligned with European priorities.
Current stage
To bring the technology to higher maturity levels by validating the solution in relevant operational environments with selected industry clients. eccenca will further develop and integrate the components into its commercial platform, Corporate Memory (CMEM), with a focus on improving intelligent data pipelines, federated data integration, and knowledge-graph-based workflow orchestration.
Unique value proposition
A scalable, privacy-preserving AI data infrastructure that combines semantic knowledge graphs + automated data pipelines + federated learning, enabling faster ML deployment, better data quality, and compliant collaboration across distributed industrial partners—integrated into eccenca Corporate Memory (CMEM).
Scalability
eccenca is scalable because its knowledge-graph-based architecture, modular data pipelines, and cloud-ready deployment enable efficient integration and processing of large, distributed datasets across organisations, industries, and infrastructures while maintaining interoperability and governance.
Sustainability
eccenca ensures sustainability by continuously integrating research outcomes into its Corporate Memory platform, supporting long-term adoption through training and services, and building a growing ecosystem around semantic data integration and trustworthy AI across industries.
Keywords
- artificial intelligence of things (aiot)
- augmented reality for shopping
- digital twin
- smart agriculture
- edge-cloud continuum
- narrowband iot (nb-iot)
- intelligence
- in factory optimisation
Research project acronyms
- CLEVER
Research projects
- Collaborative edge-cLoud continuum and Embedded AI for a Visionary industry of thE futuRe
Project identifiers
- 101097560
Contributors
- ECCENCA GMBH
Source: Horizon Results Platform