Đồ án tốt nghiệp - Developing AI-powered lead qualification call system

MINISTRY OF EDUCATION AND TRAINING
HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY AND EDUCATION
FACULTY OF INTERNATIONAL EDUCATIONG

CAPSTONE PROJECT:
DEVELOPING AI-POWERED LEAD QUALIFICATION CALL SYSTEM

ADVISOR: M.Eng. Nguyen Dang Quang
CO-ADVISOR: Mr. Vo Cao Son
EXAMINER: MSc. Nguyen Duc Khoan
STUDENTS:
Tran Binh Phuoc

21110079

Tran Duc Quang

21110793

Ho Chi Minh, May 2025

MINISTRY OF EDUCATION AND TRAINING
HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY AND EDUCATION
FACULTY OF INTERNATIONAL EDUCATION

CAPSTONE PROJECT:
DEVELOPING AI-POWERED LEAD QUALIFICATION CALL SYSTEM

ADVISOR: M.Eng. Nguyen Dang Quang
CO-ADVISOR: Mr. Vo Cao Son
EXAMINER: MSc. Nguyen Duc Khoan
STUDENTS:
Tran Binh Phuoc

21110079

Tran Duc Quang

21110793

Ho Chi Minh, May 2025

HO CHI MINH CITY UNIVERSITY OF

SOCIALIST REPUBLIC OF VIET NAM

TECHNOLOGY AND EDUCATION

Independence – Liberty – Happiness

FACULTY OF INTERNATIONAL EDUCATION

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ADVISOR EVALUATION
Student Name: Tran Binh Phuoc

Student ID: 21110079

Student Name: Tran Duc Quang

Student ID: 21110793

Major: Software Engineering
Project title: Developing AI-powered Lead Qualification Call System
Advisor: M.Eng. Nguyen Dang Quang
Co-Advisor: Mr. Vo Cao Son
EVALUATION
1. Content of the project:
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2. Strengths:
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3. Weaknesses:
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t options.
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Restricted Data Processing Capabilities: The system does not offer advanced

analytics or extended data enrichment features beyond initial qualification.
6.3.

Future Development Plan

Several areas offer potential for future improvement and expansion:
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Custom AI Model Support: Enable users to upload or fine-tune their own

models for domain-specific lead qualification.
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Advanced Analytics Dashboard: Integrate detailed analytics and insights into

pipeline performance, lead conversion rates, and AI accuracy.
-

Subion Management Module: Introduce billing integration to support

SaaS deployment and commercial scalability.
-

Multi-Language NLP Capabilities: Expand AI modules to support multiple

languages for broader global reach.
-

Omnichannel Support: Extend lead sources and communication channels (e.g.,
WhatsApp, LinkedIn, SMS) for enhanced lead engagement.

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Multi-Language NLP Capabilities: Expand AI modules to support multiple
languages for broader global reach.

104

REFERENCES
1.

Klemm, N. (2025). Ultimate Guide to Automated Lead Qualification in 2025:
Methods and Frameworks. Synthflow AI.

2.

Frontiers in Artificial Intelligence. (2025). A Review on AI-Based Business
Lead Generation and a Case Study.

3.

SalesTech Star. (2024). AI-Powered Lead Qualification: Key Benefits for Sales.

4.

IBM. (2025). AI for Lead Generation.

5.

B2B Rocket. (2025). The Future of Automated Lead Qualification: Combining
AI with Human Insight.

6.

OpenAI. (2023). OpenAI API documentation. https://platform.openai.com/docs

7.

Microsoft Azure. (2023). Azure Cognitive Services - Speech service
documentation. https://learn.microsoft.com/en-us/azure/cognitiveservices/speech-service

8.

Roy, G. M. (2023). RabbitMQ in Depth. Manning Publications.
https://www.manning.com/books/rabbitmq-in-depth

9.

Chodorow, K., &amp Dirolf, M. (2013). MongoDB: The definitive guide. OReilly
Media. https://www.oreilly.com/library/view/mongodb-thedefinitive/9781449344795/

10. Solem, A. (2023). Celery documentation. https://docs.celeryq.dev/en/stable/
11. xyflow team. (2023). React Flow documentation. https://reactflow.dev/docsss
12. Silbermann, S., Cogswell, R., Lee, Y., Alves Lima, J., Shen, D., &amp Tamboli, Z.
(2023). Material UI documentation. https://mui.com/material-ui
13. Demers, C. (2023). dnd-kit documentation. https://docs.dndkit.com
14. CrewAI
Inc.
(2024).
CrewAI
https://docs.crewai.com/introduction

documentation.

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