Voice agent fills CRM fields at 90% confidence — yet payments bounce on wrong account numbers
CoursePopular824 · reddit · 2026-10-12
A developer shared a cautionary tale of running a voice agent on collections calls. Confidence scores topped 90% and the CRM looked fine, but spot-checking recordings revealed systemic errors: a customer saying "fifteen twenty" (1520) got logged as two separate fields, and unsure names were silently replaced with phonetically similar common names. Nothing downstream caught it until payments bounced three days later.
Their fix is a validation layer between agent and CRM: regex-matching IFSC codes, length/checksum checks on account numbers, holding names when character-level confidence drops, and routing failures to a human while the caller is still on the line. Costs 1 second per field, and still only catches 70% of bad entries — values that are format-valid but belong to someone else slip through. The author argues this should be fixed at the model level, citing Gnani's approach of doing entity extraction inside the voice stack instead of transcribe-then-validate.
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