👉 Find all the templates and examples in this cheat sheet: https://bit.ly/supply-chain-cheat
In this video, I explore the usage of #n8n to build an AI agent connected to one of the analytics products designed by our startup LogiGreen.
For this first experiment, we will connect an AI Workflow to a Production Planning Module.
Discover the module here: https://apps.logi-green.com/
Github repository: https://github.com/samirsaci/production-planning
Article: https://medium.com/data-science/production-fixed-horizon-planning-with-python-8dd38b468e86
This workflow will receive demand data and production parameters (costs, units, ...) by email.
Two AI Agent nodes in the n8n workflow will parse the email, send the content to the module API endpoint and collect the results.
The agent will use the results to generate a report that will be sent back to the sender.
The objective is connect this module a specific workflow where planning teams will receive the production order by email.
What can you find in the video?
00:00 Introduction of AI Agent Experiment
00:55 Email Agent for Production Plans
01:52 Demo of the workflow
08:40 Production Planning Web Application
10:27 FastAPI Backend Presentation
11:57 AI Workflow with n8n
19:55 Demo of the ChatBot
#supplychain #n8n #aiagents #automation
