Diagnose customer churn risk from PostgreSQL data with Gemini and Slack alerts
Needs changesWhat this workflow does
This AI workflow has 17 nodes and runs on a schedule (cron 0 7 * * *) (plus 1 other trigger). Along the way it connects Postgres, Google Gemini Chat Model and Slack.
How it runs
Trigger: On a schedule (cron 0 7 * * *) (plus 1 other trigger).
- Fetch Customer Features (Postgres): run a query
- Calculate Drift Score (Code): runs custom JavaScript code
- Check AI Analysis Need (If): checks a condition and branches into true / false
- Retrieve Ticket Context (Postgres): run a query
- Combine Analysis Streams (Merge): merges the data from its input branches
- Build Evidence Payload (Code): runs custom JavaScript code
- Create Analysis Record (Code): runs custom JavaScript code
- Drift Analysis Agent (AI Agent): runs an AI agent, with model: Gemini AI Model; output parser: Parse Structured Output
- Store Assessment Result (Postgres): run a query
- Check Diagnosis Validity (Code): runs custom JavaScript code
…plus 3 more steps. See the full node list below.
Services it uses
Before you upgrade to n8n 3.0
1 thing in this workflow is removed in n8n 3.0. Fix it before you upgrade:
- AI Agent v1 (old agent modes) in Drift Analysis Agent (v1.7): replace with Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent.
| Removed in 3.0 | Replace with |
|---|---|
| AI Agent v1 (old agent modes) Drift Analysis Agent (v1.7) | Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent. |
Nodes used (10)
- Schedule Trigger
n8n-nodes-base.scheduleTrigger - Manual Trigger
n8n-nodes-base.manualTrigger - Postgres
n8n-nodes-base.postgres - Code
n8n-nodes-base.code - If
n8n-nodes-base.if - AI Agent
@n8n/n8n-nodes-langchain.agent - Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini - Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured - Merge
n8n-nodes-base.merge - Slack
n8n-nodes-base.slack
From the author
Quick overview Youtube Video: https://youtu.be/MTHAZzOZCnQ?si=0k06-RgGYHtC08v This workflow runs daily to score customer “relationship drift” from Postgres metrics, uses Google Gemini to generate a structured diagnosis for medium/high-risk accounts, stores…