about us

From Data to Insight

Shaping the Future of AI: Coupling Data and AIOps in a Virtuous Human-in-the-loop Cycle of Innovation

AI-DAPT pioneers data-centric AI solutions, reshaping industries with innovation and reliability. Our focus on AI Operations (AIOps) ensures seamless automation of data pipelines, driving trustworthy AI advancements. By integrating humans into every step, we prioritize proper data handling and model optimization. Through our approach, we bridge the gap between data and AI models, empowering industries and fostering collaboration. Join us in shaping the future of AI-driven innovation.

Progressing Beyond the State of the Art

RESEARCH AGENDA

XAI-Driven Data Operations

Elevate data processes with Explainable AI, enhancing transparency and insight across mining, exploration, and bias detection.

Collaborative Feature Engineering

Optimize feature selection through teamwork, streamlining data and enhancing AI model efficiency.

Hybrid Science-Guided Models

Combine scientific principles with AI, crafting robust models that leverage domain expertise for reliable solutions.

Sparse Model Generation

Efficiently represent complex data, minimizing resources while maintaining performance with sparse model techniques.

Adaptive AI for Model Retraining

Keep models relevant with continuous learning, ensuring effectiveness in evolving environments through adaptive AI.​

CONSORTIUM MEMBERS
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Project comprises 18 consortium members, with one coordinator overseeing collaborative efforts to advance AI technologies.

COUNTRIES
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Hailing from 7 European countries, the consortium fosters cross-border cooperation to drive innovation and address common challenges in AI development.

MONTHS
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From January 1, 2024, to June 30, 2027, the AI-DAPT project allows for comprehensive research, development, and implementation of data-centric AI solutions.

Always Innovating

Health - Non-Invasive Monitoring

AI-DAPT aims to pioneer non-invasive monitoring solutions through AI analysis of physiological signals, revolutionizing healthcare with early detection and continuous monitoring for improved patient outcomes.

Robotics & Cognitive Ergonomics

AI-DAPT enhances human-centered automation by integrating real-time worker data, optimizing productivity and safety through automated AI pipelines that predict and mitigate stress, showcasing the benefits of digitalizing human factors in industry.

Energy - Demand Response

AI-DAPT tackles energy inefficiency in buildings, implementing measures for enhanced efficiency and demand management. By integrating monitoring and ML techniques, it aims to optimize forecasts and enable personalized demand response, resulting in energy savings and reduced peak-load.

Manufacturing - Predictive Maintenance

AI-DAPT addresses predictive maintenance challenges in manufacturing, utilizing AI to forecast needs, optimize spare parts, and streamline workforce planning. Through synthetic data generation and bias detection, it delivers adaptable AI models for efficient maintenance, enhancing equipment uptime and reducing costs.

DISCOVER

Dive Deep, Stay Updated, Explore Perspectives

Introducing AI-DAPT Components: DAVE, the Pipeline Manager

DAVE is designed to simplify the way AI pipelines are created and managed.

ADRA Book Chapter Released

Advancing Trustworthy and Adaptive AI AI-DAPT Partners Contribute to the Recently Published ADRA Book The European ecosystem on Artificial Intelligence,

WEBINAR: EU AI Act

Understanding the implications for AI innovation and deployment The regulatory landscape for Artificial Intelligence in Europe is evolving rapidly. The

Advancing towards the project demonstrators

How continuous testing and validation ensure reliable integration of AI-DAPT services as the platform advances toward its demonstrators.

𝐀𝐈-𝐃𝐀𝐏𝐓 𝐃𝐞𝐦𝐨𝐧𝐬𝐭𝐫𝐚𝐭𝐨𝐫 𝟏

𝐇𝐮𝐦𝐚𝐧-𝐂𝐞𝐧𝐭𝐞𝐫𝐞𝐝 𝐀𝐈 𝐟𝐨𝐫 𝐏𝐞𝐫𝐬𝐨𝐧𝐚𝐥𝐢𝐬𝐞𝐝 𝐇𝐞𝐚𝐥𝐭𝐡𝐜𝐚𝐫𝐞 Within the AI-DAPT EU Project, the Health Demonstrator MCS Datalabs in collaboration with Charité Universitätsmedizin

Tuning 3D Printing with Hybrid Intelligence

In 3D printing, performance fails quietly, as warped geometry, brittle layers, inconsistent strength, or a part that passes inspection but

OUR NEWS

Stay Informed, Stay Ahead

ADRA Book Chapter Released

Advancing Trustworthy and Adaptive AI AI-DAPT Partners Contribute to the Recently Published ADRA Book The European ecosystem on Artificial Intelligence,

WEBINAR: EU AI Act

Understanding the implications for AI innovation and deployment The regulatory landscape for Artificial Intelligence in Europe is evolving rapidly. The

AI-DAPT Chairs Special Session on Adaptive and Trustworthy AI Pipelines at ICE IEEE/ITMC 2026

Special session on Advancing Adaptive and Trustworthy AI Pipelines at the ICE IEEE/ITMC 2026 Conference in Porto, Portugal.

AI-DAPT Newsletter #4

Building the Foundations for Trustworthy, Adaptive AI Pipelines In its fourth newsletter, AI-DAPT highlights key progress made during the first

Join us at the ADRF’25 forum

ADRF25 brings together industry leaders, researchers, and policymakers to drive forward the European agenda for responsible and human-centric AI, data,

AI-DAPT at Data Week 2025

At Data Week 2025 in Athens, the HELEN Cluster hosted a high-level thematic workshop titled “Synthetic Data: Legal, Ethical, and

OUR BLOGS

Explore, Engage, Enlighten

Introducing AI-DAPT Components: DAVE, the Pipeline Manager

DAVE is designed to simplify the way AI pipelines are created and managed.

Advancing towards the project demonstrators

How continuous testing and validation ensure reliable integration of AI-DAPT services as the platform advances toward its demonstrators.

𝐀𝐈-𝐃𝐀𝐏𝐓 𝐃𝐞𝐦𝐨𝐧𝐬𝐭𝐫𝐚𝐭𝐨𝐫 𝟏

𝐇𝐮𝐦𝐚𝐧-𝐂𝐞𝐧𝐭𝐞𝐫𝐞𝐝 𝐀𝐈 𝐟𝐨𝐫 𝐏𝐞𝐫𝐬𝐨𝐧𝐚𝐥𝐢𝐬𝐞𝐝 𝐇𝐞𝐚𝐥𝐭𝐡𝐜𝐚𝐫𝐞 Within the AI-DAPT EU Project, the Health Demonstrator MCS Datalabs in collaboration with Charité Universitätsmedizin

Tuning 3D Printing with Hybrid Intelligence

In 3D printing, performance fails quietly, as warped geometry, brittle layers, inconsistent strength, or a part that passes inspection but

Partner Spotlight: MCS

MCS Data Labs GmbH is a Berlin-based technology firm founded in 2013, specializing in turning complex data into actionable insights.

Hybrid AI Models in AI‑DAPT

Scientific knowledge with machine learning to deliver more reliable, interpretable, and data-efficient AI. By integrating physics-based models and data-driven learning,

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