Building and Automating Edge AI Systems: From AI Models Deployment to Automating Workflows with AI Agents

Join us for a hands-on workshop where you'll learn to build and automate cutting-edge edge AI systems from scratch! This interactive session will guide you through the entire process: from deploying AI models and enhancing them with Retrieval-Augmented Generation (RAG), to designing and implementing powerful agentic workflows. Discover how to use AI agents to automate complex tasks in your JavaScript applications, utilizing multi-agent pipelines and integrating third-party platform APIs, making your AI models smarter and more efficient in real-world scenarios.

Part 1: Building Your Own Edge AI System (50 minutes) – Sajan John

Overview of AI Platforms for Edge AI: Learn about popular platforms like Ollama, Hugging Face, Jan.ai, and more. Understand what each platform is good for with use case examples.

Comparison of Popular LLM Models: Explore different LLM models, their sizes, and best use cases, including lightweight models for edge AI and AI agent support.

Setting Up Ollama: Quickly set up your environment with Ollama for model deployment.

Deploying Popular Models: Deploy and run inference on popular AI models like BERT or YOLO.

Implementing RAG: Enhance your AI system with Retrieval-Augmented Generation for better performance.

API Development with Express.js and Node.js: Create a simple API using Express.js and Node.js to connect your deployed models.

Part 2: Automate Workflows with AI Agents (60 minutes) – Vikash Bhardwaj

Unlocking AI Potential: Discover how to automate workflows by enabling GenAI models to work with your custom APIs using AI agents.

Building AI Agents: Learn how to build AI agents with JavaScript and OpenAI APIs or your edge AI API, showcasing how they can handle complex tasks beyond standalone models, such as managing JIRA workflows.

Architecture and Workflow: Explore the architecture and workflow of AI agents, including defining and registering functions and tools.

Live Implementation: A practical example using the Langchain framework will demonstrate an AI agent effectively solving real-world problems.

Business Applications: Understand how to leverage AI agents to enhance business operations and streamline complex tasks.