
VCIO based description of systems for AI trustworthiness characterisation

Z-Inspection
Z-Inspection® is a methodology for assessing the trustworthiness of AI systems.



Labelling initiatives, codes of conduct and other self-regulatory mechanisms for artificial intelligence applications
AI has emerged as a critical area of interest to numerous stakeholders across the world.



IMPACT STORIES - from the TAILOR Network of Excellence Centres in AI
The TAILOR Impact Stories is a powerful demonstration of the collective achievements and spirit of the TAILOR network.

STRATEGIC RESEARCH & INNOVATION ROADMAP OF TRUSTWORTHY AI
This document is the first version of the Strategic Research and Innovation Roadmap of the TAILOR project, focussed on Trustworthy Artificial Intelligence through Learning, Optimization and Reasoning.


Handbook of Trustworthy AI
The main goal of the Handbook of Trustworthy AI (HTAI) is to provide to non-experts, researchers and students, an overview of the problem related to the developing of ethical and trustworthy AI systems.

C3 Generative AI
C3 Generative AI uses agents to retrieve data, analyze information, surface insights, and orchestrate workflows to drive business value.

The AI PaaS For Deploying, Managing, and Scaling Apps
Heroku is your gateway to building, deploying, and scaling AI-powered applications without the operational complexity. As an AI PaaS, Heroku gives developers the infrastructure, tools, and managed services needed to bring AI apps to life faster.

Deploy.AI
With Deploy.AI's advanced RAG framework embedded throughout your workflows, you can customize how AI finds and uses your data—ensuring agents always have the right context for accurate, relevant responses.

Human activity recognition in time series in PIR sensor networks with reinforcement learning
Recognizing human activity from IoT events is essential for automatic light scene setting. A challenge with IoT systems is the diversity among customers.

EdgeAI: Leveraging SNNs, Transformers, and Autoencoders for Near-Sensors Intelligence
This talk will explore the cutting-edge advancements in EdgeAI for biosignal analysis, focusing on innovative algorithms such as Spiking Neural Networks (SNNs), Transformers, and Autoencoders.

Functional and Non-Functional Requirements in Edge Ai Systems
This presentation highlights the critical elements defining edge AI solutions’ performance and effectiveness.