AI Powered Sales Assistant

AI-Powered Sales Assistant with STT & Avatar Interaction

This innovative AI-based project is designed to help companies train their sales teams more effectively. The solution features a highly interactive avatar powered by advanced Large Language Models (LLMs) to simulate real-life customer interactions.

Client & Industry Background

Our client, a leading retail and e-commerce company, wanted to enhance their sales training process using AI-driven real-time customer simulations. Their primary challenge was inconsistent sales performance, as many employees struggled to handle customer queries effectively.

They envisioned an AI-powered virtual sales assistant that could:

Simulate real customer interactions using speech-to-text (STT) technology.

Provide real-time feedback on sales conversations.

Offer data-driven insights to improve communication skills.

Challenges & Pain Points

1. Inconsistent Sales Training

Traditional role-playing exercises lacked scalability and consistencyTrainers could not provide real-time feedback on sales conversations

2. Lack of Data-Driven Insights

Sales managers had no concrete metrics to assess salesperson performanceNo insights into conversation fluency, response time, or key phrases used.

3. Need for a Scalable Solution

The company required a cost-effective, AI-driven solution to train employees at scaleSalespeople needed hands-on practice without requiring human trainers

The Solution: AI-Powered Sales Assistant

We developed an AI-driven sales assistant that utilizes speech-to-text (STT) technology to engage with salespeople in simulated conversations. The system provides real-time analysis, tracks performance metrics, and offers actionable feedback for improvement.

Frontend (React.js)

Azure STT API – Converts user speech into text

WebSockets – Enables real-time data streaming.

Pixel Streaming Infrastructure – Provides high-quality AI avatar video

React-Record-Webcam – Records conversations for analysis.

React-Timeline-Editor – Visualizes conversation structure

React-Chart.js – Displays sales performance trends.

Backend (Python & AI Processing)

FastAPI / Django – API for real-time STT processing.

NLP-based Analysis – Assesses conversation quality & engagement.

PostgreSQL / MongoDB – Stores user data & conversation logs.

AI-Powered Sentiment & Speech Analysis – Evaluates tone & speech fluency.

Implementation & Features

1. Avatar Simulation

A virtual avatar acts as a customer, engaging sales personnel in realistic product discussions.

2. Performance Evaluation

Conversations are analyzed to assess key traits such as communication skills, product knowledge, confidence, and overall performance.

3. Comprehensive Reporting

Generates detailed performance reports with actionable insights for trainees.

4. Azure Integration

Utilizes Azure Speech-to-Text (STT) technology for accurate and seamless conversation processing.

Technical Stack

Python

Flask

React.js

PostgreSQL

Impact & Results

Improved Sales Performance

34% faster response times in customer conversations.21% increase in customer engagement due to improved sales pitch.

Data-Driven Training Decisions

Improved Sales Performance Managers gained real-time insights into salesperson strengths & weaknesses.React-Chart.js dashboards allowed for performance tracking & progress reports.

Scalable & Cost-Effective Training

Eliminated the need for human trainers in early sales training phases.Allowed simultaneous training for 100+ salespeople using AI simulations.

Conclusion

" By implementing AI-driven sales training, the company transformed its onboarding & coaching process. Sales reps practiced real scenarios, received instant AI feedback, and improved their customer interactions significantly "

" The combination of STT, WebSockets, AI analysis, and interactive UI components made this a scalable and data-driven solution for sales training at scale "