Architecture

Layer	Responsibility	Output
Audio intake	Accept a call recording and optional known-speaker clips.	meeting.wav, Agent=agent.wav
Pipeline runner	Validate inputs, encode references as data URLs, call OpenAI, and write artifacts.	Run metadata and output directory
Diarization	Call gpt-4o-transcribe-diarize with response_format="diarized_json" and chunking_strategy="auto".	Speaker-labeled segments
Transcript normalization	Convert API output into consistent JSON and Markdown with stable segment IDs.	transcript_segments.json, speaker_labeled_transcript.md
Meeting intelligence	Extract summary, decisions, actions, risks, explicit questions, suggested follow-ups, quotes, and follow-up email with structured evidence references.	meeting_intelligence.json, meeting_brief.md
Guardrails and review gate	Redact sensitive fields, verify evidence references, optionally moderate content, and route risky outputs for review.	guardrail_report.json

This is intentionally request-based. The Realtime API is a better fit for live voice UX, browser capture, or telephony streaming. For durable post-call diarization, this pattern uses the Transcriptions API and then runs structured extraction over the speaker-labeled transcript.