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💡 Reservation Event Log

AI-powered reservation insights in Slack

The Idea

Turn your reservation event logs into instant, human-readable summaries using natural language. Drop a reservation ID in Slack, get back a complete AI-generated timeline of the guest's journey—from booking to checkout.

How It Works

The Flow:

  1. Slack receives natural language input: "Show me what happened with reservation ABC123"
  2. n8n workflow extracts the reservation ID and calls the Event Log API
  3. Event data flows into an LLM with a structured prompt
  4. AI generates a chronological summary with actors, event sources and key context
  5. Slack delivers the formatted timeline back to your team

What You Get

A complete audit trail that reads like a story:

  • Who did what and when (actor tracking)
  • Payment history, room assignments, key access events
  • Check-in/out flows, door access attempts, task completions
  • All from a single JSON boundary—clean, complete, contextual

Perfect For

  • Support teams investigating guest issues
  • Operations reviewing reservation timelines
  • Auditing workflows and compliance tracking
  • Training staff with real guest journey examples

Technical Details

Event Log Filter Endpoint

The workflow uses the Event Log Filter API to retrieve all events for a specific reservation:

Endpoint: 

GET /event-logs/filter

Query Parameters:

  • objectIds - Filter by booking ID and/or reservation ID (can accept multiple values)
  • limit - Maximum number of events to return (default: 100)
  • offset - Pagination offset (default: 0)

Example Request: 

GET /event-logs/filter?objectIds=booking-123&objectIds=reservation-456&limit=100&offset=0

The API returns an array of business events containing: - Event metadata (ID, timestamp, topic, object type) - Actor information (who triggered the event) - Event source (which system generated it) - Contextual data (payments, room assignments, key access, etc.)

LLM Processing

The workflow aggregates all events into a single JSON and passes it to the LLM with a structured prompt that requests:

  • Chronological event ordering
  • Actor and source identification for each event
  • Key context extraction (payments, rooms, access)
  • Human-readable summary output

Key APIs

Third-Party Technologies

This use case leverages:

  • n8n - Workflow automation platform for orchestrating the event processing pipeline
  • Slack - Team messaging platform for natural language input and result delivery
  • LLM Options - Popular language models for generating summaries:

Sample Output

Example request in Slack: 

Show me what happened with reservation RES-12345

AI-generated timeline:

Reservation Journey for RES-12345

Booking Created (06:53 UTC)

  • Actor: Guest (John Doe) via GUEST_JOURNEY
  • Source: IBE (Internet Booking Engine)
  • Payment: Visa card ending in 1111 authorized for 0 CHF (free rate plan)
  • Stay: 1 adult, arrival Oct 28, departure Oct 29
  • Rate Plan: for_free

Profile Matching (06:53 UTC)

  • Actor: INTEGRATION via PERSON_RECORD_MATCHING
  • Source: PLATFORM
  • Details: Existing guest profile matched (219 previous reservations)
  • Guest Data: Address, birthdate (Jun 15, 1985), ID (P1234567), nationality (US), license plate (AB123CD) synchronized

Notification Sent (06:53 UTC)

  • Actor: INTEGRATION via NOTIFICATION
  • Source: EMAIL channel
  • Recipient: john.doe@example.com
  • Template: RESERVATION_CREATED

Reservation Condition Assessed (06:53 UTC)

  • Actor: INTEGRATION via PLATFORM
  • Source: Automated condition check
  • Status: MINOR (requires attention)
  • Reasons: Guest flow not started, ID check pending
  • Booking Channel: IBE
  • Payment Method: Credit Card

Pre-Check-In Flow Started (06:54 UTC)

  • Actor: Guest (John Doe) via GUEST_JOURNEY
  • Progress:
    • 06:54:12 UTC - ADDRESS page confirmed
    • 06:54:17 UTC - SERVICES page confirmed
    • 06:54:21 UTC - PAYMENT page confirmed
    • 06:54:21 UTC - Pre-check-in flow completed

Door Access Configured (06:54 UTC)

  • Actor: Guest (John Doe) via GUEST_JOURNEY
  • Source: Door access sync
  • Status: KEYS_CONFIRMED, access state set to NONE
  • Details: Digital keys ready for activation upon room assignment

Room Assignment (06:54 UTC)

  • Actor: Staff (Jane Smith) via BACKOFFICE
  • Source: Manual assignment
  • Room: Unit 301 (clean, unoccupied)
  • Action: Room 301 assigned to reservation, confirmed in PMS

Reservation Condition Updated (06:54 UTC)

  • Actor: Guest (John Doe) via GUEST_JOURNEY
  • Source: Flow completion trigger
  • Status: Guest flow started, "not yet started" condition removed

Ready to build? Check out the Event Consumption Guides to start capturing events.