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Build an Agentic RAG Customer Service Chatbot with CrewAI

BeginnerGuided Project

Build a Retrieval-Augmented Generation (RAG) and Agentic AI chatbot with CrewAI. Apply in-demand skills to solve real-world challenges with AI, leveraging LLMs. Create and orchestrate AI agents, work with databases, and refine prompt engineering for a customer service application used by a restaurant. This hands-on project is a necessity for all software engineers and machine learning engineers seeking to level-up their skills, in only 30-minutes!

Language

  • English

Topic

  • Artificial Intelligence

Skills You Will Learn

  • Artificial Intelligence, Generative AI, Python, CrewAI, Agentic RAG

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 30 minutes

Platform

  • SkillsNetwork

Last Update

  • June 3, 2025
About this Guided Project
In today's rapidly evolving technological landscape, mastering fundamental AI concepts like Retrieval-Augmented Generation (RAG) and Agentic AI is no longer optional—it's essential for any aspiring software engineer or machine learning engineer trying to get their foot in the door. Businesses face challenges responding to clients' queries: teams spending endless hours answering repetitive questions that waste their valuable time. This project offers you a unique opportunity to build a customized, efficient chatbot that solves such real-world problems, allowing staff to focus on true value-adding tasks. By completing this guided project, you'll gain practical, hands-on experience in building intelligent systems that can revolutionize customer interactions and streamline operations.

Who Should Enroll

  • Anyone interested in learning about AI agents and fundamental machine learning concepts like Retrieval-Augmented Generation (RAG)
  • Those looking to build specialized chatbots for domain-specific applications such as customer service, technical support, or other interactive use cases
  • Developers and tech enthusiasts seeking to gain practical experience with in-demand AI technologies

Why Enroll

This hands-on project delivers essential, high-demand skills that define today's technology sector. In just 30 minutes, you'll gain practical experience building AI solutions through clear visual demonstrations and accessible explanations. The course accommodates both newcomers to AI concepts and experienced developers seeking to solidify their understanding of these foundational technologies. By the end, you'll have both theoretical knowledge and practical implementation skills that are immediately applicable to real-world projects.

A Look at the Project Ahead

Upon completing this 30-minute beginner-friendly lab, you will be able to:
  • Build a customer service chatbot using CrewAI and LLMs
  • Deploy AI agents with specific roles, tools, and knowledge sources
  • Extract context from PDFs using Retrieval Augmented Generation (RAG)

RAG Process

What You'll Need

You will build your project using the IBM Skills Network Labs, a virtual lab environment that will provide you with everything you need to complete your project. The only thing you need is a modern web browser like Chrome, Firefox, Edge, or Safari. If you would like to showcase your project or deploy it in production for others to use, we recommend deploying it to the IBM Cloud® Code Engine or a similar fully managed serverless or Kubernetes service.


Instructors

Abdul Fatir

Data Scientist

Abdul specializes in Data Science, Machine Learning, and AI. He has deep expertise in understanding how the latest technologies work, and their applications. Feel free to contact him with questions about this project or any other AI/ML topics.

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Contributors

Karan Goswami

Data Scientist

I am a dedicated Data Scientist and an AI enthusiast, currently working at IBM's Skills Builder Network. Learning how some simple mathematical operations could be used to make predictions and discover patterns sparked my curiosity, leading me to explore the exciting world of AI. Over the years, I’ve gained hands-on experience in building scalable AI solutions, fine-tuning models, and extracting meaningful insights from complex datasets. I'm driven by a desire to apply these skills to solve real-world problems and make a meaningful impact through AI.

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Matthew Wu

Marketer at IBM

Supporting Cognitive Class and IBM through digital marketing and tailored content creation

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Faranak Heidari

Data Scientist at IBM

Detail-oriented data scientist and engineer, with a strong background in GenAI, applied machine learning and data analytics. Experienced in managing complex data to establish business insights and foster data-driven decision-making in complex settings such as healthcare. I implemented LLM, time-series forecasting models and scalable ML pipelines. Enthusiastic about leveraging my skills and passion for technology to drive innovative machine learning solutions in challenging contexts, I enjoy collaborating with multidisciplinary teams to integrate AI into their workflows and sharing my knowledge.

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