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Case Study: AI & Speech Platform

AI Voice Interview Portal

An end-to-end AI voice interview platform for high-volume recruiting. Candidates complete guided voice sessions; audio is transcribed in real time and evaluated against custom rubrics.

AI VoicePlatform
80%Workload Cut
98%Recovery Rate
5 WeeksDuration
Application Architecture

Speech Pipeline & Real-Time Rubric Scoring

Project Overview

High-volume recruiting requires screening hundreds of applicants, which typically overwhelms HR teams. The AI Voice Interview Portal solves this bottleneck by conducting guided screening calls asynchronously in-browser.

Our studio shipped the web platform (Next.js), hook-ups for client-side audio streaming via WebSockets, and automatic translation/transcription services using Whisper models. Audio is transcribed and evaluated against customizable rubrics, presenting recruiters with auditable LLM evaluation scores.

Key Deliverables

  • Guided real-time audio recording in-browser utilizing secure WebAudio layers.
  • Real-time audio streaming and speech-to-text transcription via WebSocket tunnels.
  • Bespoke candidate evaluation using LLM-backed rubrics with clear audit traces.
  • Comprehensive recruiter dashboards to track pipelines, review transcripts, and filter scores.
  • Resilient audio socket session recovery protecting data against user connection drops.

Technologies Used

WebSocketsFastAPIOpenAI WhisperGPT-4 APIReact / Next.jsPostgreSQLTailwind CSSRedis

Client Value

Client SectorEnterprise HR / Speech AI
Workload Cut80% Screening
Eval SpeedUnder 2s / response

The Challenge

Transmitting raw audio streams in real time from diverse browsers without package drops. Re-establishing the active session context gracefully if the candidate’s network connection was temporarily disconnected mid-interview.

The Solution

Created a custom WebAudio chunking engine streaming 500ms audio buffers over WebSocket lines. Configured a Redis-backed session state layer that auto-buffers audio locally in IndexedDB, syncing pending chunks upon connection recovery.

Measurable Results

80%Phone-Screen Load Saved
98%Session Recovery Rate
1.8sAudio-to-Score Latency

Interested in Similar Capabilities?

Discuss speech processing pipelines, WebSocket streaming, LLM-based evaluation metrics, or recruiter workflows.

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