Identifying and mapping corrosion represents a significant challenge in maintaining oil production systems. Mechanical and chemical phenomena, such as abrasion and hydrogen attack, cause corrosion on the internal surface of pipes. Knowing the dimensions of corrosion enables technicians to make decisions about the structural stability of pipelines under operating conditions. Using ultrasound imaging is a non-destructive approach to assessing the state of internal surfaces. We present a web application for processing ultrasound signals and image reconstruction. However, it can be used in any non-destructive ultrasound inspection application. The software is developed mainly in Python and Typescript, using a different approach than conventional web applications. Instead of using a standard structure, with the front-end running in the browser and the back-end running the data processing on a remote server, our application runs entirely on the browser through Pyodide, a Python distribution for the browser and Node.js based on WebAssembly whilst the server side only hosts the web application files. The application is divided into modules for (i) graphical interface, (ii) reading inspection files, (iii) signal preprocessing, (iv) estimation of inspection parameters, (v) external surface detection (for inspection by immersion), and (vi) image reconstruction. The web application allows Python script execution and offers a user-friendly interface for running image reconstruction algorithms. This paper describes the development of critical features and indicates the chosen implementation of algorithms. The current state of development is presented, and the next steps toward the ultimate goal of corrosion mapping are defined.