Developer ships three browser-based AI tools, documents bugs found along the way

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A developer built WeConvertIt, a platform offering image, PDF, and audio tools — including background removal, stem separation, and speech-to-text — that run entirely in the browser without uploading files to a server. During development, a stem-splitting tool using Meta's HTDemucs model produced physically impossible output, with some audio stems exceeding 174% of the original signal's magnitude, which revealed the third-party ONNX model file itself was defective rather than the pipeline code. The developer resolved this by exporting a fresh ONNX model from the official checkpoint and validating it against a reference implementation before shipping. A separate bug in ONNX Runtime caused outright session failures in the Whisper-based speech-to-text feature due to tied embeddings in quantized models, an upstream issue beyond the developer's direct control. A third challenge involved browser memory limits surfacing only on longer audio files, highlighting the unique constraints of running AI models entirely client-side.

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