📊 Automated real-time web research with Gemini AI and SerpAPI search
⚡ 3,228 views · 📊 Market Research & Insights
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Description
This workflow demonstrates how to automate live information gathering, fact-checking, and trend analysis in response to any chat message - using a powerful AI agent, memory, and a real-time search tool.
Use cases are many: This is perfect for researchers needing instant, up-to-date data; support teams providing live, accurate answers; content creators looking to verify facts or find hot topics; and analysts automating regular reports with the freshest information.
How It Works
- The workflow is triggered whenever a chat message is received (e.g., a user question, research prompt, or data request).
- The message is sent to the AI Agent, which follows the following steps:
- First, it queries SerpAPI – Research to gather the latest real-time information and data from the web.
- Next, it checks the Window Buffer Memory for any related past interactions or contextual information that may be useful.
- Finally, it sends all collected data and context to the Google Gemini Chat Model, which analyzes the information and generates a comprehensive, intelligent response.
- Then, the AI Agent delivers the analyzed, up-to-date answer directly in the chat, combining live data, context, and expert analysis.
How To Set Up
- Download and import the workflow into your n8n workspace.
- Set up API credentials and tool access for the AI Agent:
- Google Gemini (for chat-based intelligence) → connected to Node Google Gemini Chat Model.
- SerpAPI (for real-time web and search results) → connected to Node SerpAPI - Research.
- Window Buffer Memory (for richer, context-aware conversations) → connected to Node Window Buffer Memory.
- Open the chat in n8n and type the topic or trend you want to research.
- Send the message and wait for the process to complete.
- Receive the AI-powered research reply in the chat box.
Requirements
- An n8n instance (self-hosted or cloud).
- SerpAPI credentials for live web search and data gathering.
- Window Buffer Memory configured to provide relevant conversation context in history.
- Google Gemini API access to analyze collected data and generate responses.
How To Customize
- Choose your preferred AI model: Replace Google Gemini with OpenAI ChatGPT, or any other chat model as preferred.
- Add or change memory: Replace Window Buffer Memory with more advanced memory options for deeper recall.
- Connect your preferred chat platform: Easily swap out the default chat integration for Telegram, Slack, or any other compatible messaging platform to trigger and interact with the workflow.
Need Help?
If you’d like this workflow customized, or if you’re looking to build a tailored AI Agent for your own business - please feel free to reach out to Agent Circle. We’re always here to support and help you to bring automation ideas to life.
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🔗 Nodes Used
AI Agent, OpenAI Chat Model, Simple Memory, SerpApi (Google Search), Manual Chat Trigger, Google Gemini Chat Model
📥 Import
Download workflow.json and import into n8n:
Workflow menu → Import from File