Build an Ai Scheduler: Smart Meetings with Zoom, LlamaIndex & Qdrant @ AWS
Build an Ai Scheduler: Smart Meetings with Zoom, LlamaIndex & Qdrant @ AWS
Please note that attendees require a photo ID to enter the venue. This event will also be streamed for those of you who cannot join us in San Fransisco.
The Qdrant team, in partnership with AWS, LlamaIndex and Zoom invites you to the AWS AI Engineering Loft where we will show you hands on how to build a state of the art RAG application. Simon Suo, Co-Founder and CTO at LlamaIndex will give the closing talk.
During this one-day event, you’ll learn how to build a Retrieval-Augmented Generation (RAG) recommendation engine specifically designed to enhance meeting productivity.
By leveraging Qdrant as a Vector Database, LlamaIndex as our LLM Framkework and the Zoom APIs for data, you'll create a system that recommends future meetings to attend based on missed content—ensuring you stay connected to topics of interest.
Zoom's Developer Platform empowers teams to build collaborative applications by integrating with its highly scalable video and communication infrastructure. It enables the development of immersive, real-time collaboration tools and enhances virtual experiences across sectors.
LlamaIndex is a powerful tool for managing and querying large datasets, offering an intuitive interface for integrating machine learning models. It simplifies the process of building retrieval-augmented generation (RAG) systems, enabling developers to create more sophisticated and responsive agents.
Qdrant is an industry-leading vector database and a semantic search engine, powering large operations such as Twitter, Discord, Firefox, Tripadvisor, Johnson & Johnson, Deloitte, and more.
Agenda:
9:00 AM - Doors Open
9:00-10:00 AM - Networking + Breakfast
10:00-11:00 PM - Workshop: Building on Qdrant with Thierry Damiba
10:00-11:00 PM - Qdrant + Cursor Walkthrough with Thierry Damiba
12:00-1:00 PM - Lunch Break
1:00-2:00 PM - Workshop: Building an Interactive Chatbot on Zoom with Ojus Save
2:00-3:00 PM - Open Coding Session
3:00-4:00 PM - Closing Talk from Simon Suo
Learning Objectives:
Understand the fundamentals of RAG and its application in meeting recommendations.
Gain practical experience using the Zoom APIs to build a custom RAG recommendation engine.
Learn how to fine-tune models to improve the relevance and accuracy of recommendations.
Key Topics:
Introduction to RAG:
Overview of RAG and its benefits in recommendation systems.
Zoom APIs and Chatbots:
Step-by-step guide on integrating and utilizing various APIs from Zoom and building a RAG Chatbot.
Building the Engine:
Best practices for developing a recommendation engine that analyzes missed meetings.
Model Fine-Tuning:
Techniques for enhancing recommendation accuracy based on user preferences and meeting content.
Target Audience:
This workshop is designed for developers, data scientists, and AI practitioners interested in building practical AI applications for improving meeting effectiveness.
Hosts:
Zoom Team
LlamaIndex Team
Qdrant Team