Predict tenant default risk with GPT-4o, Gmail, Slack and collections APIs
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 14 nodes and runs on a schedule (every day at 02:00). Along the way it connects OpenAI Chat Model, Gmail, Slack and BambooHR and 2 more.
How it runs
Trigger: On a schedule (every day at 02:00).
- Workflow Configuration (Edit Fields (Set)): sets 7 fields: rentPaymentApiUrl, creditBureauApiUrl, employmentApiUrl…
- Fetch Credit Bureau Data (HTTP Request): calls an HTTP API
- Get a rent payment item (PayPal): work with payout item
- Fetch Employment Records (BambooHR): get many
- Merge Tenant Data (Edit Fields (Set)): sets 3 fields: rentPaymentData, creditBureauData, employmentData
- Risk Analysis AI Agent (AI Agent): runs an AI agent, with model: OpenAI Chat Model; output parser: Risk Score Output Parser
- Route by Risk Level (Switch): routes items into 3 branches
- Send High Risk Alert Email (Gmail): uses Gmail
- Send Medium Risk Notification (Slack): uses Slack
- Trigger Automated Collection (HTTP Request): calls an HTTP API (POST)
…plus 1 more step. See the full node list below.
Services it uses
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (12)
- Schedule Trigger
n8n-nodes-base.scheduleTrigger - Edit Fields (Set)
n8n-nodes-base.set - HTTP Request
n8n-nodes-base.httpRequest - AI Agent
@n8n/n8n-nodes-langchain.agent - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured - Switch
n8n-nodes-base.switch - Gmail
n8n-nodes-base.gmail - Slack
n8n-nodes-base.slack - BambooHR
n8n-nodes-base.bambooHr - PayPal
n8n-nodes-base.payPal - Airtable
n8n-nodes-base.airtable
From the author
How It Works This workflow automates tenant screening by analyzing payment history, credit, and employment data to predict rental risks. Designed for property managers, landlords, and real estate agencies, it solves the challenge of objectively evaluating…