The AMBEATion Methodology

The main components of the methodology envisioned by AMBEATion are shown below.

AMS Back-End

The AMBEATion project targets the automation and optimization of Analog Mixed-Signal (AMS) integrated circuit design.

Artificial Intelligence

The project's goal is to use Artificial Intelligence (AI) and Machine Learning (ML) techniques to improve AMS design productivity.


The final result of the project will be a scriptware-based flow, integrated with commercial state-of-the-art Electronic Design Automation (EDA) tools.

The AMBEATion project aims at developing new methodologies and software for the Electronic Design Automation (EDA) of Analog-Mixed-Signal (AMS) semiconductor devices. Thanks to the use of Machine Learning (ML) and Artificial Intelligence (AI), these methodologies, which will be integrated in state-of-the-art industrial tools and flows, will help in overcoming the productivity limitations of current AMS design.

AMBEATion Consortium


The AMBEATion consortium includes three academic partners and two multi-national companies, participating in the project with multiple entities.


Read the latest news and updates on the AMBEATion project

Official Press Release

Marie Skłodowska-Curie Actions Research and Innovation Staff Exchange H2020-MSCA-AMBEATion-2020 The partners who have joined in a new EU-funded research project within the call H2020 Marie Skłodowska-Curie Actions announce the beginning of the international and multisciplinary Read more…


For questions about the project, please contact the Coordinator's office at the address below:

Dipartimento di Automatica e Informatica - Ufficio Progetti, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129, Turin (TO), Italy