Block 1 - OpenAI Chat Model
- Type / Role
- @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
- Config choices
- Version 1.2
This workflow is provided as-is. Please review and test before using in production.
What problem does this workflow solve? Call centers often record conversations for quality control and training, but reviewing every transcript manually is tedious and inefficient. This workflow ...
@n8n/n8n-nodes-langchain.lmchatopenai, n8n-nodes-base.splitinbatches, n8n-nodes-base.scheduletrigger, n8n-nodes-base.googlesheets, n8n-nodes-base.set, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.outputparserstructured, n8n-nodes-base.stickynote
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by InfyOm Technologies.
Original n8n.io sourceCall centers often record conversations for quality control and training, but reviewing every transcript manually is tedious and inefficient. This workflow automates sentiment analysis for each call, providing structured feedback across multiple key categories, so managers can focus on improving performance and training.
The workflow will append results in new columns automatically:
https://docs.google.com/spreadsheets/d/1aWU28D_73nvkDMPfTkPkaV53kHgX7cg0W4NwLzGFEGU/edit?gid=0#gid=0
This workflow is ideal for:
If you want deeper insight into every customer interaction, this workflow delivers quantified, actionable sentiment metrics automatically.
Just connect:
β¦and this workflow will automatically turn your raw call transcripts into actionable sentiment insights.
This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
| Workflow | Automate call center sentiment analysis with GPT-4o-mini and Google Sheets |
|---|---|
| Complexity | intermediate |
| Nodes | 9 |
| Categories | AI Summarization, Multimodal AI |
| Author | InfyOm Technologies |
| Published | 20 Aug 2025 |
Use the JSON export at /data/workflows/7624/7624.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
What problem does this workflow solve? Call centers often record conversations for quality control and training, but reviewing every transcript manually is tedious and inefficient. This workflow ...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your AI Summarization, Multimodal AI use case.