AI Integration with Peek Pro SMS Notifications

AI integration connects directly to Peek Pro's webhook and API layer, listening for booking lifecycle events like booking.created, booking.updated, and booking.cancelled. The primary data objects are the Booking, Customer, and Activity. An AI agent intercepts these events, determines the appropriate SMS communication based on pre-defined templates and real-time context, and orchestrates the outbound message via a service like Twilio or MessageBird. For two-way flows, the agent also processes inbound SMS replies, parsing intent to trigger actions like check-in confirmations or simple Q&A.

Implementation focuses on three high-value surfaces: pre-arrival confirmations, last-minute operational updates, and post-experience feedback collection. For example, an AI agent can automatically send a personalized confirmation SMS 24 hours before a tour, including a dynamic Google Maps link and weather advisory. If a guide is running late, the system can ingest a Slack alert, use an LLM to draft a clear, empathetic update, and send it via SMS to affected customers, all while logging the event back to the Peek Pro booking notes for audit.

Rollout requires a phased approach, starting with read-only, one-way confirmations before enabling two-way interactions. Governance is critical: all AI-generated messages should pass through a human-in-the-loop approval queue for the first 30 days, with clear opt-out language and rate limits to prevent spam. The system must maintain a complete audit trail, linking every SMS to the specific Peek Pro booking ID and the AI prompt/context used to generate it. This ensures reliability and provides a feedback loop for continuous improvement of the AI's tone and accuracy.

The integration connects at two primary points within Peek Pro's API and webhook ecosystem. First, the Booking Created and Booking Updated webhooks serve as the event source, triggering the AI notification pipeline. Second, the system interacts with Peek Pro's Customer and Booking objects via the REST API to fetch real-time details like contact info, activity specifics, and guide assignments. The AI layer sits as a middleware service, subscribing to these events, processing the data, and orchestrating outbound communication through a provider like Twilio or MessageBird.

A typical workflow for a last-minute change notification involves:

• Peek Pro fires a booking.updated webhook with a payload containing the new time and booking ID.
• The AI service retrieves the full booking record and customer phone number via the Peek Pro API.
• An LLM generates a personalized, context-aware SMS (e.g., "Hi [Name], your [Activity] start time has moved to 2:30 PM due to weather. Your guide, Maria, will meet you at the dock. Reply 'OK' to confirm or 'HELP' for assistance.").
• The message is queued, sent via the SMS gateway, and the customer's reply is ingested, classified by intent (e.g., confirmation, question, opt-out), and can trigger automated follow-ups or create a support ticket in Peek Pro.

For production rollout, implement rate limiting aligned with Peek Pro's API quotas and use a persistent queue (e.g., Redis or Amazon SQS) to handle notification bursts during peak booking times. Governance is critical: maintain an audit log of all generated messages and customer replies, and implement a human-in-the-loop review for high-stakes communications like cancellations or sensitive itinerary changes. Use feature flags to control rollout by customer segment or notification type, ensuring reliability before full deployment.

Integrating AI with Peek Pro's SMS notification system requires a secure, event-driven architecture. The core pattern listens for booking lifecycle webhooks (e.g., booking.created, booking.updated) from Peek Pro, triggering an AI orchestration layer. This layer, built on serverless functions or a lightweight microservice, calls an LLM API (like OpenAI or Anthropic) with a structured prompt containing the booking data, customer profile, and notification intent. The generated message is then validated against a content safety policy and sent via a transactional SMS provider like Twilio or MessageBird. All message payloads, AI prompts, and customer opt-in statuses are logged to an audit trail for compliance.

A phased rollout is critical for managing risk and gathering feedback. Start with low-risk, high-volume notifications like booking confirmations, where the AI's role is limited to personalizing pre-approved message templates. Monitor deliverability, customer response rates, and support ticket volume. Phase two introduces AI for dynamic content generation, such as crafting last-minute update messages based on weather or traffic conditions. The final phase enables two-way AI communication, where inbound SMS from customers (e.g., "Running late" or "Need to reschedule") is processed by an AI agent to interpret intent, query the Peek Pro API for availability, and draft a relevant response for human review before sending.

Governance is enforced through prompt templates, output classifiers, and RBAC. Prompt templates ensure consistency and prevent prompt injection by separating booking data from instructions. A secondary classifier model can scan all AI-generated messages for brand voice, accuracy, and safety before dispatch. Access to modify prompts or bypass the review queue should be restricted via role-based controls within your integration platform. For operators in regulated markets (e.g., EU GDPR), ensure AI message generation is documented as part of your data processing records and that customer consent for SMS communications is explicitly managed within Peek Pro's customer fields or a linked CRM.