Why is Read AI so slow to transcribe long meetings?

CRM_Hopper_Alt · 2026-08-01T23:20:55Z

Just spent another 30 minutes watching the little spinner after uploading a 90-minute client call. Read AI's transcription finally chugged into my inbox like it was delivered by carrier pigeon. For a tool with "AI" in the name, it seems to have missed the memo on processing speed. Is this a universal experience, or am I just cursed? I've tried it with different file types (MP4, MOV, even a clean MP3) and the pattern holds: anything over 45 minutes becomes a serious bottleneck. My workflow grinds to a halt. Compare this to some other platforms where transcription, while not perfect, is at least *fast*. Some observations from my pain: * The delay isn't linear. A 30-minute file is okay. A 60-minute file feels like it takes triple the time, not double. * No clear status during processing. Just "processing" with no ETA or progress bar. Classic black box. * It's not my connection. I've got gigabit fiber, and other cloud services scream. I'm starting to suspect it's an architectural issue. Are they batching everything into a single, overloaded queue? Using a slower, but marginally more accurate, engine for long-form audio? The lack of transparency is the real kicker. If it's going to be slow, just tell me it'll be ready in 2 hours so I can move on with my life. Anyone else hitting this wall, or found a workaround? I want to like it for the summary features, but this is a fundamental workflow killer.

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benchmark_bob_42

(@benchmark_bob_42)

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03/08/2026 9:15 am

You're absolutely right about the SLAs. I pulled theirs after a particularly frustrating 90-minute wait last month. The SLA only guarantees uptime, not processing time. The specific language is "availability of the processing request endpoint," not the completion time. So they're technically meeting their guarantee even if your file sits in a backlog for hours.

This is why reproducible benchmarks are so important. I've started logging submission timestamps, file durations, and completion times for every service I test. The pattern for Read AI specifically shows a clear knee in the curve around the 45-minute mark, which strongly supports the separate, under-provisioned batch pipeline theory.

-- bb42

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