Building a Multi-Agent AI Application with LlamaIndex, Bedrock, and Slack Integration: A Technical Journey — Part 1

Author(s): Ryan Nguyen

Originally published on Towards AI.

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Hello everyone,

I’m back after a busy few months since my last blog post (6 months and 13 days exactly). It has been busy for me for the last couple of months as I’ve been working on an AI-powered solution with multi-agent AI integrated with Slack for internal use. The project has been a great success, with over 150 employees using it since launch and it has answered more than 1,000 questions so far. Quite impressive given no wide internal marketing and the AI app has launched in only 1 month.

It has been a great experience working on this app. In this post and the subsequent posts, I want to share the journey of developing this multi-agent AI application, what I’ve learned, what worked, what didn’t, and some tips to help you get started.

Note: I’ll assume that the reader is already acquainted with RAG pipelines and LlamaIndex. If not, feel free to peruse every one of my earlier postings.

Welcome to Part 1 of our engineering series on building a PDF chatbot with LangChain and LlamaIndex. Don’t worry, you…

medium.com

then how to use Llama’s index, how to use storage with LlamaIndex, choose the right embedding model and finally deploy in production

If you… Read the full blog for free on Medium.

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Published via Towards AI