Indian English Accent: Recogniser Changes
Indian English includes many phonetic systems shaped by mother-tongue transfer. We explain how we changed our speech recogniser to reduce caller misinterpretation.
The Ringg team covers call quality, CRM links, operating patterns, and lessons from our work.
Indian English includes many phonetic systems shaped by mother-tongue transfer. We explain how we changed our speech recogniser to reduce caller misinterpretation.
Three teams tested Ringg with their existing call lists during early access. The results after the first month.
A CRM webhook fires. When does Ringg reach the lead? We tracked the full handoff and located the bottleneck.
Most support call failures come from architecture, not the model. These are the four patterns we see most often.
Call duration does not show quality. We tracked four metrics tied to positive outcomes.
See the ops stack when AI handles volume and a small team manages exceptions.
The step-by-step reasoning Ringg uses when a caller says something the script did not anticipate.
Flows, objects, field mapping, and the permission setting that breaks many Salesforce integrations.
We annotated a real qualifying call from opening to close: key moments, why they worked, and what could cause failure.
Routine support calls follow familiar paths. When AI handles them, human agents can focus on exceptions.
At 800 milliseconds, callers begin to notice the gap. We break down latency at each pipeline stage and show where time is spent.
The problem we kept seeing in outbound sales teams, and why voice AI seemed suited to address it.