Partner Spotlight: WITSIDE

Based in Greece, WITSIDE is a premier software and consulting house dedicated to “Intelligence for Business.” With a deep expertise in Advanced Analytics, Data Management, and Business Intelligence, WITSIDE specializes in turning raw data into actionable insights.

WITSIDE’s Role in AI-DAPT

WITSIDE’s role in AI-DAPT is pivotal: ensuring that the project’s sophisticated AI pipelines don’t just work in a lab but integrate seamlessly into the real-world platforms that industries rely on every day.

WITSIDE’s philosophy is rooted in the belief that technology is more than just a tool—it is a force for transformation. While other partners focus on the scientific foundations of hybrid models, WITSIDE focuses on usability and market viability. WITSIDE acts as the interface between the project’s scientific innovations and the practical demands of the market.

WITSIDE’s contribution to AI-DAPT is strategic and multifaceted, focusing on two major pillars: Integration and Exploitation.

Integrating AI-DAPT into the Real World.

One of the biggest challenges in AI adoption is the “silo” effect—innovative new tools often fail because they don’t “talk” to the legacy systems businesses already use. WITSIDE leads Task 4.5: Integration of AI-DAPT in Existing AI Solutions & Platforms. Its goal is to ensure that the AI-DAPT framework isn’t an isolated island. Instead, WITSIDE are working to integrate the project’s automated pipelines with:

  • Open-source platforms: Such as Jupyter Notebooks, which are the bread and butter of data scientists worldwide.
  • Commercial platforms: Including enterprise-grade analytics suites (like Qlik, or the S5 Enterprise Analytics Suite) and other market-standard tools.

By doing this, WITSIDE ensures that a data scientist in a manufacturing plant or a health clinic can use AI-DAPT’s advanced features (like synthetic data generation or model observability) without having to abandon their familiar working environments.

Defining the Path to Market

Innovation without a business model is merely invention. WITSIDE leads the Exploitation Management for the entire project. This means WITSIDE is responsible for defining how AI-DAPT will survive and thrive after the project concludes. This work involves:

  • Market Analysis: Understanding the current landscape of DataOps and MLOps to position AI-DAPT effectively.
  • Business Modeling: Creating sustainable business plans for the AI-DAPT platform as a whole, as well as individual exploitation plans for each partner.
  • IPR Handling: Managing Intellectual Property Rights to ensure that the innovations produced are protected and commercially viable.

Data Management Expertise

Beyond management and integration, WITSIDE contributes its deep technical know-how to the project’s Data Management Services. Leveraging its experience with global technology leaders like Qlik, WITSIDE assists in designing the Data Pipeline Execution Engine, ensuring that data flows efficiently, securely, and reliably through the AI-DAPT system.

Key Personnel

Stelios Genouzos brings over 20 years of expertise in the business intelligence industry to the AI-DAPT consortium, serving as a vital link between technical innovation and market application. Within WITSIDE, he helps drive the project’s Exploitation Management, ensuring that the automated AI pipeline frameworks are translated into sustainable, commercially viable business models. His deep understanding of technology trends and end-to-end solution delivery is instrumental in guiding the integration of AI-DAPT’s services into existing real-world platforms, empowering businesses to seamlessly adopt data-centric AI technologies.

Looking Ahead

For WITSIDE, AI-DAPT is an opportunity to push the boundaries of what’s possible in Data and AI pipelines. By embedding their “real-world application” DNA into the project, they are helping to guarantee that AI-DAPT will deliver a solution that is not only scientifically robust but also commercially powerful—empowering businesses to harness the full potential of their data with trust and efficiency.

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