We are proud to announce that Nowon has received official approval and funding from Innosuisse, the Swiss Innovation Agency. This support marks a significant milestone for our work and underlines the relevance of our technology at a national level.
Innosuisse is the Swiss Confederation’s agency for innovation promotion. Its mission is to strengthen Switzerland’s position as a leading innovation hub by supporting ambitious research and development projects with clear market potential. Funding decisions are based on rigorous expert evaluations, focusing on technological novelty, feasibility, and economic impact.
Receiving Innosuisse approval means that a project has passed a highly selective process and is recognized as technologically innovative, strategically relevant, and economically promising.
Public innovation funding is not granted lightly. Being supported by a federal innovation agency sends a strong signal of trust, both in the underlying technology and in the team behind it. For us, this approval confirms that the challenges we are addressing in live music recognition and copyright remuneration are not only industry-relevant, but also of broader importance for Switzerland’s innovation landscape.
The funded project focuses on pushing the boundaries of music recognition, particularly in complex and real-world environments. Live performances, reinterpretations, covers, and noisy settings pose challenges that go far beyond traditional audio identification.
By combining advanced AI-based music recognition with deep domain knowledge from the live music and rights management ecosystem, we aim to:
improve robustness and accuracy in challenging audio conditions,
better distinguish between different versions of musical works,
and make music usage measurable where it has historically been difficult to document reliably.
This research-driven approach allows us to go beyond incremental improvements and address fundamental limitations of existing systems.
Alongside live music recognition, the project also addresses the growing impact of AI-generated music on the music ecosystem. As generative models become increasingly capable of producing music at scale, new challenges arise around attribution, transparency, and copyright remuneration. In many cases, AI-generated tracks are difficult to classify, lack clear authorship, or imitate existing styles, making it harder to determine how they should be handled within established rights management frameworks.
Within this project, we examine how AI-generated music can be identified, analyzed, and differentiated from human-created performances. The focus lies on understanding characteristic patterns, usage contexts, and implications for monitoring and reporting, rather than treating AI outputs as an opaque black box.
By bringing AI-generated music under closer scrutiny, the project aims to contribute to clearer boundaries and more informed decision-making for collecting societies, platforms, and rights holders. This work complements our core research in music recognition by ensuring that emerging forms of music creation are considered alongside traditional live performances, helping future-proof copyright remuneration systems in an increasingly hybrid musical landscape.
The Innosuisse approval provides us with the opportunity to further develop our technology in close alignment with research partners and industry stakeholders. It allows us to invest deeply in innovation while maintaining a strong focus on practical impact.
We see this as an important step toward building the next generation of music recognition technology, contributing to fairer copyright remuneration and a more transparent live music ecosystem.
