Healthcare · ML Pipeline
A healthcare ML pipeline that turns doctor-patient conversations into structured medical notes using speech recognition, language models and AWS services.
Project profile
The challenge
Clinical conversations contain the information needed for documentation, but turning each consultation into a useful structured note adds administrative work. The system needed to handle audio processing and language-model steps as a traceable production pipeline.
The solution
An end-to-end workflow was built to process consultation audio with local Whisper speech recognition and use language models to organize the transcript into medical notes. Queue-based cloud components separate stages so work can be processed and monitored reliably.
What was delivered
Business outcome
The resulting pipeline connects raw consultation audio to structured documentation through a clear sequence of services, reducing the need to move content manually between transcription and note-generation tools.
Related capability
Custom retrieval-augmented generation systems that help teams and customers get grounded answers from approved documents, data and knowledge bases.
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