ADR Awareness Centre

Alteryx, Inc. is a software company that provides self-service data analytics software. The company was founded in 1997 and is headquartered in Irvine, California, and has more than 8,000 customers worldwide.

DataRobot delivers AI that maximizes impact and minimizes business risk. Our AI applications and platform integrate into core business processes so teams can develop, deliver, and govern AI at scale.

Dataiku is the platform for Everyday AI, enabling data experts and domain experts to work together to build data into their daily operations, from advanced analytics to Generative 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.

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

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.

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.

Recognizing human activity from IoT events is essential for automatic light scene setting. A challenge with IoT systems is the diversity among customers.

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.

This presentation highlights the critical elements defining edge AI solutions’ performance and effectiveness.

In today’s fast-evolving technological landscape, edge AI stands at the forefront of innovation, enabling data processing at the edge, closer to the source of information.

This paper outlines the initial FPGA-centric endeavors within the EdgeAI project, targeting scenarios where extremely constrained power-energy parameters intersect with the demand for high performance and accuracy in executing Artificial Intellige