Summarize SE Ranking AI search visibility using OpenAI GPT-4.1-mini
Needs changesWhat this workflow does
This AI workflow has 8 nodes and runs manually, when you click “Execute workflow”. Along the way it connects OpenAI Chat Model. It also calls api.seranking.com over HTTP.
How it runs
Trigger: Manually, when you click “Execute workflow”.
- Set the Input Fields (Edit Fields (Set)): sets 3 fields: target_site, engine, source
- SE Ranking AI Request (HTTP Request): calls api.seranking.com
- SE Ranking AI Summarizer (Information Extractor): extracts structured fields from text with AI, with model: OpenAI Chat Model
- Enrich Data (Code): runs custom JavaScript code
- Create a Binary Data (Function): runs custom JavaScript (legacy Function node)
- Write File to Disk (Read/Write Files from Disk): writes a file to disk
Services it uses
HTTP calls to: api.seranking.com
Before you upgrade to n8n 3.0
1 thing in this workflow is removed in n8n 3.0. Fix it before you upgrade:
- Function (legacy) in Create a Binary Data: replace with Code node, mode 'Run Once for All Items'.
Rather not rewrite it? Many of these flows can be rebuilt in Make (free plan).
| Removed in 3.0 | Replace with |
|---|---|
| Function (legacy) Create a Binary Data | Code node, mode 'Run Once for All Items' |
Nodes used (8)
- Manual Trigger
n8n-nodes-base.manualTrigger - Edit Fields (Set)
n8n-nodes-base.set - HTTP Request
n8n-nodes-base.httpRequest - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Information Extractor
@n8n/n8n-nodes-langchain.informationExtractor - Code
n8n-nodes-base.code - Read/Write Files from Disk
n8n-nodes-base.readWriteFile - Function
n8n-nodes-base.function
From the author
This workflow automates AI-powered search insights by combining SE Ranking AI Search data with OpenAI summarization. It starts with a manual trigger and fetches the time-series AI visibility data via the SE Ranking API. The response is summarized using OpenAI…