Smart Sales AI: Real-Time Intent Detection And Adaptive Responsive System

J Srikanth Reddy; Bandela Jaswanth; Karumanchi Rohith Kumar; Pidugu Swanith Kumar Reddy; Kalluru Madhu Priya

Smart Sales AI: Real-Time Intent Detection And Adaptive Responsive System

Author(s)	J Srikanth Reddy, Bandela Jaswanth, Karumanchi Rohith Kumar, Pidugu Swanith Kumar Reddy, Kalluru Madhu Priya
Country	India
Abstract	AI is transforming businesses at a remarkable pace, and it's no different for sales and customer relationship management. In today's demanding and quickly evolving environment, it's crucial for sales people to have smooth conversations. However, real-time interaction can be very challenging for them when it comes to understanding customer sentiment and finding the key discussion points, resulting in missed business. To overcome this challenge, the project "AI-Powered Sales Call Assistant using Real-Time Voice Analysis" provides a smart system which aids a user through a conversation. This system receives calls, analyzes conversations in real time, and presents helpful information such as customer sentiments, key discussion points and response recommendations, helping users to converse more confidently and make smart decisions. This project uses LiveKit to access live voice data and then FastAPI for background operations to facilitate intelligent analysis of the call via Google Gemini and then render helpful insights onto a user-friendly interface created using React and Tailwind CSS. The conversations are saved on MongoDB to access for future analysis. Instead of getting feedback about a conversation after the call, this intelligent assistant uses voice data in real-time and can also assess what a customer's intent is (if interested, uncertain, or confused) and suggest the best way to respond to them. Though this project only supports English conversations currently, it can be upgraded to support multiple languages, analyze sentiments in real-time and even integrate with CRM systems. In conclusion, this project effectively demonstrate how AI technology can improve conversations by enhancing the way salespeople engage with customers.
Keywords	Artificial Intelligence, Natural Language Processing, Real-Time Voice Analysis, Sentiment Analysis, Customer Intent Detection, Conversational AI, Sales Automation, Decision Support System, Speech-to-Text Processing, Adaptive Response Generation.
Field	Engineering
Published In	Volume 7, Issue 2, March-April 2026
Published On	2026-04-27

View / Download PDF File

E-ISSN 3048-7641

doi

CrossRef DOI is assigned to each research paper published in our journal.

AIJFR DOI prefix is
10.63363/aijfr

Downloads

Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 7 Isu 2 Cover Page Vol 7 Isu 1 Cover Page Vol 6 Isu 6

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA

About AIJFR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9898-79-39-59	editor@aijfr.com

Advanced International Journal for Research

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Smart Sales AI: Real-Time Intent Detection And Adaptive Responsive System

Share this