AI call summaries from our power dialer are about 60% accurate. Who's actually solved this?
6-person insurance agency. ran outbound on aircall for 3 months, then orum for 2 months. both have AI summary features that promise 95%+ accuracy and in practice deliver around 60-70%. our SDRs end up rewriting summaries half the time, which kills the productivity claim entirely.
the failure modes we see most: multi-speaker calls confuse the AI (any call with a spouse or partner on the line tanks accuracy), industry jargon gets transcribed phonetically not semantically, the summary is a chronological recap not an outcome record (useless for CRM activity logging), and accents push accuracy below 50% on our southern and midwest customers.
the thing none of the vendors talk about: most of these tools transcribe FIRST, summarize SECOND. so any transcription error compounds into the summary. anyone using a system where the LLM is fed structured CRM context BEFORE the call connects, so the summary at the end is contextual not just transcriptive? that's the angle i havent found in any of the major US vendors yet. curious if anyone has cracked this with a smaller or non-US player.