Podcast Master
The challenge
Section titled “The challenge”Podcast distribution platforms (Apple Podcasts, Spotify, etc.) have strict requirements for audio format, loudness levels, and metadata. Creators often deliver raw audio files that are too quiet, too loud, or missing cover art and episode information. Manually processing each episode through multiple tools is tedious and error-prone.
The approach
Section titled “The approach”Podcast Master is a native desktop application built in Rust that handles the entire podcast preparation pipeline in a single step. Select your audio file, fill in the metadata, and the app produces a distribution-ready file with correct loudness, format, and embedded cover art.
The processing pipeline:
- Loudness analysis — Measures the input audio against broadcast standards (LUFS targets)
- Volume adjustment — Normalises the audio so your podcast sounds consistent alongside other shows
- Format conversion — Outputs in the correct codec and container format for podcast platforms
- Metadata embedding — Embeds title, artist, cover art, and episode information directly into the file
Features
Section titled “Features”- One-Click Processing — Select audio, fill the form, and get a distribution-ready file
- Loudness Normalisation — Matches podcast platform loudness standards automatically
- Cover Art Embedding — Attach artwork directly to the output audio file
- Metadata Management — Title, artist, episode number, and description embedded in the file
- Native Performance — Built in Rust for fast processing without Electron overhead
Tech Stack
Section titled “Tech Stack”| Language | Rust |
| Audio Processing | Native DSP (loudness metering, gain adjustment) |
| Platform | Desktop (macOS, Linux, Windows) |
| Build | Cargo |
The result
Section titled “The result”A focused tool that solves a real workflow problem for podcast creators. Instead of juggling FFmpeg commands, loudness meters, and metadata editors, the entire preparation step happens in one native app.
This project demonstrates building production audio tools with clear user workflows — the same approach I bring to client projects where end-users need reliable, straightforward audio processing.
Source Code
Section titled “Source Code”The source code is available on the project’s GitHub repository.