Multi-AI Agent Chatbot for Postgres/Supabase Databases and QuickChart Generation Who is this for? This workflow is ideal for data analysts, developers, and business intelligence teams who need an AI-powered chatbot to query Postgres/Supabase databases and generate dynamic charts for data visualization. What problem does this solve? It simplifies data exploration by combining conversational AI with database querying and chart generation. Users can interact with their database using natural language, retrieve insights, and visualize data without manual SQL queries or chart configuration. What this workflow does AI-Powered Chat Interface: Accepts natural language prompts to query databases or generate charts. Routes user requests through a tool agent system to determine the appropriate action (query or chart). Database Querying: Executes SQL queries on Postgres/Supabase databases based on user input. Retrieves schema information, table definitions, and specific data records. Dynamic Chart Generation: Uses QuickChart to create bar charts, line charts, or other visualizations from database records. Outputs a shareable chart URL or JSON configuration for further customization.
Tags
Call n8n Workflow ToolWHTTP Request
OpenAI Chat Model
Postgres Chat Memory
Structured Output ParserRelated workflows
See all AI Automation→
WScrape and score Amazon products with Apify, OpenAI, and Google Sheets
Quick overview This workflow manually scrapes product results from an Amazon search URL via the Apify Amazon Crawler actor, uses OpenAI to generate a structured product analysis (category, key feature, verdict, value score), and appends the enriched results to a Google Sheets spreadsheet. How it works Runs when you manually click “Test workflow” in n8n. Sends the configured Amazon search URL and scraping limits to the apify Amazon Crawler actor and retrieves the dataset items. Filters out any scraper items that are missing a title or contain an error. Uses OpenAI to analyze each product’s title, brand, price, rating, and review count and returns a structured category, key feature, buyer verdict, and 1–10 value score. Combines the scraped fields and AI analysis into a single row format and adds a timestamp. Appends each enriched product as a new row in Google Sheets. Setup Create an apify API token and add it as an HTTP Header Auth credential used by the Apify request. Add an OpenAI API key as an OpenAI credential and choose the model to use in the configuration. Connect a Google Sheets OAuth2 account and select the target spreadsheet, sheet tab, and columns for appending rows. Upda
Suggest meeting slots using AI
The purpose of this n8n workflow is to automate the process of identifying incoming Gmail emails that are requesting an appointment, evaluating their content, checking calendar availability, and then composing and sending a response email. Note that to use this template, you need to be on n8n version 1.19.4 or later.
SAI agent chat
This workflow employs OpenAI's language models and SerpAPI to create a responsive, intelligent conversational agent. It comes equipped with manual chat triggers and memory buffer capabilities to ensure seamless interactions. To use this template, you need to be on n8n version 1.50.0 or later.