AI voice performance platform hero

NDA project

AI Voice Performance (AIVP) Platform

AI-powered system that analyzes in-store customer conversations, scores service quality, and highlights performance gaps — without storing voice data to ensure compliance.

Industry

Retail / Sales Operations

Country

US

Platform

Hardware + Web SaaS

Partnership model

Turnkey Product Development

Client Context

The client operated a network of physical retail locations, where sales performance depended heavily on how staff interacted with customers. There were clear service standards: greeting, needs discovery, upsell, closing. Quality control relied on: manual audits, random checks, mystery shopping. This created several problems:

  • only a small % of interactions was reviewed
  • feedback was delayed and subjective
  • top-performing and underperforming employees were hard to identify

The client needed a way to systematically evaluate every interaction, without increasing compliance risk or operational overhead.

Challenge

  • Operational Pain: Manual QA processes couldn’t scale across multiple locations

  • Technical Limitation: Need to analyze conversations without storing or exposing sensitive audio data

  • Business Risk: Missed revenue due to inconsistent service and lost upsell opportunities

  • Compliance Constraint: Strict requirements around data privacy and voice recording

AI voice performance platform demo

Solution

We developed a hybrid AI system that captures and analyzes customer interactions in real time — without storing raw voice data. Audio is processed locally and then passed through an AI pipeline that:

  • detects speech activity
  • separates speakers
  • converts speech to text in-memory
  • analyzes conversation structure using LLM

The system evaluates each interaction against predefined service criteria (e.g., greeting, upsell, closing) and assigns a score. Results are aggregated and displayed in a dashboard. This allows managers to quickly identify where standards are followed — and where performance drops.

Team

  • 2x

    AI
    Engineer

  • 1x

    Fullstack Developer

  • 1x

    UI/UX Designer

  • 1x

    Hardware Specialist

  • 1x

    Project Manager

  • 1x

    QA
    Engineer

  • 2x

    AI
    Engineer

  • 1x

    Hardware Specialist

  • 1x

    Fullstack Developer

  • 1x

    Project Manager

  • 1x

    UI/UX Designer

  • 1x

    QA
    Engineer

What We Delivered

  • End-to-end voice analytics system (hardware + software)

  • AI pipeline for conversation analysis (VAD, ASR, diarization, LLM)

  • Conversation scoring based on service standards

  • Dashboard with performance insights by location and employee

  • Privacy-first processing (no raw voice storage)

  • Flexible setup for different retail environments

Timeline & Cost

Full breakdown is available under NDA

Discovery & Planning: 3–4 weeks

Architecture & Design: 4–6 weeks

Development: 4–6 months

Total Timeline: ~6–8 months

Discovery Phase: $25K–$40K

Design & Architecture: $40K–$70K

Development: $180K–$320K

Total Investment: $300K–$450K

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Impact & Results

Operational:

Reduced time spent on manual quality control

Technical:

Enabled large-scale analysis of conversations without storing sensitive audio

Business:

Improved service consistency and identified missed revenue opportunities across locations

Technology Stack

  • Python
  • VAD
  • ASR
  • Diarization
  • OpenAI
  • AssemblyAI
  • FastAPI
  • React
  • Raspberry Pi
  • Jetson
  • and more...

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