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ServiceUpdated on 12 January 2026

Interpretable AI and Advanced Statistical Modeling for Industrial Excellence

CEO at Datharsis

Granada, Spain

About

Datharsis provides high-level technical expertise for international research consortia, specializing in leading or subcontracting Work Packages (WPs) dedicated to Data Modeling, Interpretable Machine Learning, and Advanced Analytics. We transform complex industrial datasets into validated evidence for real-time decision-making, moving beyond "black-box" AI to provide solutions that human operators can trust and act upon.

Our services cover the entire data lifecycle within the Cluster 4 framework:

  • Experimental Design (DoE): We optimize data collection in industrial environments to maximize signal-to-noise ratios, ensuring that Digital Twins are built on reliable, high-quality foundations.

  • Interpretable AI & Advanced Multivariate Analysis: We specialize in uncovering hidden patterns in process industries. Our models don't just predict; they explain the "why" behind equipment failures or production bottlenecks, supporting the Next-Generation AI Agents and Agile Robotics initiatives.

  • Digital Twin Intelligence: We provide the analytical core for Local Digital Twins, integrating multi-modal data streams for early warning systems, predictive maintenance, and crisis preparedness.

  • Data Governance & Compliance: We ensure that all data processing pipelines are efficient and fully compliant with the European Data Act, supporting sovereign and secure data sharing within consortia.

By integrating Datharsis, your project benefits from our unique Strategic Partnership with the CoDaS Lab (University of Granada), combining academic rigor with agile, market-ready software development. We provide comprehensive technical reports, interactive visualization dashboards, and the statistical validation necessary for high-impact dissemination and industrial scaling.

Type

  • Development
  • Consulting
  • Research

Organisation

Datharsis

Start-Up

Granada, Spain

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