Technical Guide: Creating Agents for Real-Time Data Analysis
Introduction The ability to process and act on constantly changing information is what separates a basic agent from an advanced automation tool. In this post, we will look at how to configure a workflow that allows your agents to consume, interpret, and report data in real-time. Architecture Components Data Source: The origin of the information (third-party APIs, web scraping via tools like Apify, or a data stream in Google Sheets). Orchestration Layer: The brain that connects the source to the model (we will use n8n or Make). AI Model: The intelligence responsible for processing raw JSON or text (Gemini or Claude). Output Layer: Where the agent delivers the analysis (Slack, email, a Google Sheets dashboard, or automatic social media updates). Implementation Steps Connecting the source: Configure an "HTTP Request" node in your automation platform to consume the API endpoint. Define the polling frequency based on data criticality. Preparing the con...