Case Study
A closer look at how this system was designed, architected, and rolled out in production. Each section below captures one part of the delivery story—from scoping and UX to data pipelines, integrations, and ongoing operations.
The product is optimised for teams that need to localise or transform large volumes of audio and video. We modelled typical production pipelines and designed the interface so editors can queue, preview, and approve batches of content instead of working one file at a time.
Under the hood, jobs pass through stages for speech recognition, translation, voice cloning, and mastering. We exposed job state through a simple status model so both the UI and third-party integrations always know where each asset sits in the pipeline.
Side-by-side waveform and caption views help editors quickly spot issues. We built controls for region-based re-synthesis, custom pronunciation dictionaries, and version history so teams can iterate without fear of losing work.
The system is tuned for enterprise workloads: bursty traffic, large assets, and multiple concurrent projects. Storage, compute, and queue capacity scale independently so costs remain predictable even as throughput grows.