Architecture for GPU-free audio transcription in fintech moderation pipelines

A proposed design for SaaS fintech moderation recommends an asynchronous, provider-neutral transcription adapter for classifying audio reports before human review. Original audio and a job record are stored first, then submitted through a narrow interface that returns either a transcript or a typed failure. Moderation consumes only a versioned text artifact, and provider choice stays behind the adapter boundary. The author argues that clearly separating states such as timeouts, rejected formats, empty transcripts, and outages prevents incomplete text from being mistaken for authoritative results. The approach aims to keep the contract stable as providers change, rather than promising identical behavior across them.