About Us

WHY STELLA SONORIS AND WHO WE ARE?

Stella Sonoris was designed to offer an immersive and enriching sound experience, fostering deep relaxation and heightened dream awareness.
This application is the result of a thoughtful collaboration between distinct creative minds, each contributing their unique expertise to shape a meaningful and finely crafted project.

Loïk Brédolèse (Alias Óneiroi): Loïk initiated the project. As a music teacher with years of meditation practice, he handled the design, music composition, and sound design of the application. Meydän: A professional composer, Meydän enhances the application with his original compositions. His varied practice in meditation shines through in his music, offering users a deep and beneficial sound experience. Alessandro Sperotti: An exceptional developer and coder, Alessandro programmed the entirety of the application. His work ensures a smooth, immersive, and flawless user experience, thanks to his technical expertise.

ART

Loïk Brédolèse: Founder of the project, Loïk is a music teacher, composer, and designer with extensive experience in meditation. He led the artistic direction of the app, overseeing its overall design, music composition, sound design, and the careful curation of reliable scientific studies.
Meydän: A professional composer, Meydän contributes original music that enriches the app’s soundscape. His deep meditation practice is reflected in his compositions, offering users a profoundly calming and immersive auditory experience.

Beyond the artistic and scientific aspects, technical development played a crucial role in the success of Stella Sonoris. Managing real-time audio processing, sensor data integration, and ensuring a seamless user experience required a precise and innovative approach. A key technical challenge was the ability to deliver different types of audio signals during REM sleep phases — a feature that demanded both responsiveness and reliability from the app’s architecture.

DEVS

Óneiroi
Keyvich Solution

Maxime Haurel
Alessandro Sperotti
Jaafar Maher

We would also like to thank the National Sleep Research Resource (NSRR) for granting us accreditation. The access to their high-quality clinical datasets has significantly strengthened the scientific foundation of the project, and allow us to refine our algorithms and improve the accuracy of REM phase detection through real-world, validated sleep data.

AND WHAT'S NEXT?

Our approach is empirical, which means we will improve the application as we use it daily, but also thanks to the feedback you provide us on Discord, then if you have any great ideas, don't hesitate to join us!