The broader roadmap now sits here, with the earlier links and sections grouped into one dedicated page.
This roadmap supports Dunes Inn & Suites, Sea and Breeze Hotel and Condo, Atlantis Inn, Tybee Sandcastle Inn, and Admiral’s Inn on Tybee Island.
Once the pricing pilot is validated, the following hotel AI projects can follow.
Automate pre-arrival, upsell, and service-response messaging with AI-guided personalization.
Cluster guest feedback, identify trends, and surface property-level action items for management.
Route maintenance issues, prioritize urgent requests, and track recurring room issues across hotels.
Generate campaigns, pricing bundles, and direct-booking promotions based on occupancy and seasonality.
These are the broader capabilities that support future hotel AI pilots after the pricing engine MVP.
Prioritize hotel use cases, define ROI, and plan rollout by property and team.
Unify reservations, occupancy, market, and event data into a clean operating layer.
Upgrade from rules-based pricing into demand prediction and optimization over time.
Launch guest-service copilots, review summarizers, and internal hotel operations assistants.
The roadmap keeps the architecture modular so that data, pricing, and automation layers can scale cleanly.
Start with linked CSV files and a fast Python pipeline for pilot velocity.
Show price actions, occupancy, demand, and property-level operational metrics.
Replace rules with learned models while keeping the same frontend output contract.
