Essentia.js, a port of the popular Open-Source C++ library Essentia, comes to the web world to become the reference library to use together with the Web Audio API. Whilst there are many libraries for audio analysis and feature extraction in native computing languages, this Master thesis exposes the need of such a library in JavaScript, and proposes Essentia.js as the best option to cover those needs. The Music Information Retrieval community needs this tool to be able to develop software and research using web technologies, to continue evolving and stay in the state of the art. Having compiled the C++ library into a JavaScript audio analysis library, a study on the efficiency of the library is carried out by benchmarking the execution of algorithms available in Essentia.js and comparing them to their equivalents from Meyda.js, a library written in JavaScript. Also, an application designed to be integrated into a production environment is developed using Essentia.js to detect audio problems in music files uploaded to a website. Helping improve the efficiency of the quality control process for digital music distribution. The difficulties found in the process are enumerated and the solution developed is described and demonstrated. These steps, described in this Master Thesis, are part of a bigger project by the Audio Signal Processing Lab at Music Technology Group of the Universitat Pompeu Fabra, to turn Essentia into Essentia.js and ensuring the quality of the library.