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Triage WhatsApp clinic requests with OpenAI, Slack, and Data Tables

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Created by: Intuz || intuz
Intuz

Last update

Last update 2 days ago

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Quick overview

This workflow receives patient WhatsApp messages via WAHA, uses OpenAI to extract structured administrative triage details, stores each case in an n8n Data Table, posts human-review items to Slack, and either replies with safe clinic info or runs scheduled Slack follow-ups until the clinic team closes the case.

How it works

  1. Receives inbound WhatsApp messages via a WAHA webhook (or a manual test trigger) and filters out outbound, group, and empty events.
  2. Normalizes the payload and sends the message text to OpenAI to classify intent, urgency, and whether the case requires human review, returning a strict JSON result.
  3. Builds a case record (including follow-up settings) and upserts it into the n8n Data Table named “Clinic Demo Cases”.
  4. If human review is required, posts the case details to a Slack channel for escalation (either tagged for Dot review or marked as n8n-owned fallback monitoring) and sends an acknowledgement back to the patient via WAHA.
  5. If human review is not required, sends the schema-validated administrative reply back to the patient via WAHA.
  6. Runs every 10 minutes to find due n8n-owned cases in the Data Table, uses OpenAI to generate a structured operational reminder, posts it to Slack, and updates reminder counters and status until max reminders are reached.
  7. Accepts clinic staff updates through an n8n Form, updates the corresponding Data Table row, and posts a confirmation to Slack to stop further scheduled reminders.

Setup

  1. Add an OpenAI credential and select it in the OpenAI Chat Model used by both the triage and follow-up reminder steps.
  2. Add a Slack credential and set the target channel (for example, #clinic-escalations) in all Slack message steps.
  3. Set up WAHA and create an HTTP Header Auth credential with header X-Api-Key, then update the WAHA base URL and configure WAHA to send inbound messages to the workflow’s webhook URL.
  4. Create or update the n8n Data Table “Clinic Demo Cases” to include the required columns (including monitoring fields like monitor_owner, next_followup_at, reminder_count, and max_reminders).
  5. Review “Workflow Configuration” values (especially coordinationMode, reminderIntervalMinutes, and maxReminders) and keep the Clinic Case Update Form URL private for internal use.

Requirements

  • n8n – Workflow automation orchestrator.
  • WAHA – Receives WhatsApp messages and sends patient responses.
  • OpenAI – Provides structured administrative classification and fallback reminder decisions.
  • Dot – Proactive agent responsible for monitoring Slack cases, following unresolved responsibilities, escalating important cases, and preparing summaries.
  • Slack – Shared coordination channel for initial escalations, Dot monitoring, fallback reminders, and case updates.
  • n8n Data Table – Stores cases, monitoring ownership, reminder state, team notes, and resolution status.
  • n8n Form Trigger – Provides the internal Clinic Case Update Form.
  • Credentials – OpenAI, Slack OAuth, and WAHA X-Api-Key credentials must be configured.
  • Dot setup – Dot must have access to #clinic-escalations and must confirm its monitoring responsibility.
  • Demo safety – Dummy patient data should be used until applicable privacy, access-control, consent, retention, security, and regulatory requirements are completed.

Additional info

Additional info
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