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70%
false-positive reduction (50% → 15%)

70% False-Positive Reduction with AI Voice Interviews — Published by Retell AI

Retell AI published how our team integrated their voice stack in 48 hours and cut false-positive assessment rates by 70%: third-party, verifiable proof of our voice AI engineering.

Read the published case study ↗
50% → 15%
false-positive assessment rate
48 hours
integration to production
70%
reduction, verified in a published vendor case study

The problem

AccioJob's assessment funnel had a 50% false-positive rate: candidates who passed automated coding tests but failed live technical interviews. Every false positive cost recruiter time, client trust, and interview slots. The root cause: static assessments can be gamed, and typing-based tests don't verify understanding.

The build: 48 hours to production

We added a conversational AI voice interviewer as a verification layer after the coding round. Candidates explain their reasoning out loud; the agent probes with adaptive follow-ups, the 'why?' chain that's nearly impossible to fake. Neeraj integrated Retell AI's voice stack into the existing event-driven assessment pipeline in 48 hours, including scoring rubrics and recruiter-facing evidence reports.

The result

False positives fell from 50% to 15%, a 70% reduction, published by Retell AI as an official case study. Later, we re-architected the voice layer onto our own LiveKit stack, cutting per-minute cost from ~10¢ to 2.5¢ while preserving assessment quality.

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