AI That Runs the Guest Experience.
Every review, every post-stay touchpoint, every unanswered message is a missed opportunity. Eagle Eye automates the guest relationship so your team can focus on hospitality.
Guests tell you exactly what went wrong. Usually after they have gone.
Hospitality runs on reviews in a way few other industries do. A rating shift moves occupancy and rate directly, and the feedback that drives it arrives on a dozen platforms at all hours, written by people who have already left.
The response window that matters is short. A thoughtful reply within a day reads as attentiveness; the same reply a fortnight later reads as damage control. Most properties miss it not through indifference but because the person who would write it is running the floor.
The same applies to the guest you would like back. Almost nobody works that list systematically.
Agents built for hospitality.
DEPLOYED AGENTS
Review Response Engine
Intercepts and neutralizes reputation threats in real-time.
Social Media Platform
Multi-location social presence operated by a single intelligence layer.
Customer Capture Layer
Passive intelligence gathering from physical location traffic.
Review Tracker
Real-time reputation surveillance across all locations.
After deployment.
Every platform watched, every review answered
Booking sites, review platforms, and social channels monitored together, with responses drafted while the stay is still recent.
Problems escalated while they are still fixable
Negative feedback routed to a manager immediately rather than surfacing in a monthly report.
Social presence maintained across properties
One layer operating multiple locations without a marketing hire per site.
Past guests contacted on purpose
Re-engagement driven by stay history and season rather than by whoever has time to build a list.
The systems you already run.
Property management systems vary wildly and many are closed. We integrate where there is an API and work from exports where there is not, the audit establishes which you are dealing with.
Two weeks, start to live.
Friction audit
We map where the hours actually go, not where you think they go. For a property this usually means the general manager and whoever currently owns the review response, if anyone does. The output is a ranked list of targets scored on time cost and reversibility. We start with high-time, easy-to-undo work.
Systems connected
Review and booking platforms connect first, because response time is the number that moves rating fastest. Nothing is published yet. The first agent runs in shadow mode, producing output that only your team sees, so you can judge the quality against work you already trust.
Approval queues live
Positive reviews commonly auto-publish within a fortnight; anything describing a service failure stays with a manager permanently. Anything sensitive routes to a human queue before it goes out. You decide what auto-publishes and what waits for a person, and you can move that line at any point.
Handover
Every agent gets a named owner on your side, a documented rollback, and a metric agreed before the build started. If the number does not move, we said what it was in advance and there is nowhere to hide.
What operators ask first.
How long before anything is actually live?
Two weeks to a working deployment. The first three days are a friction audit, the next four connect your systems and run the first agent in shadow mode, and the second week moves it into production behind approval queues. You see real output in week one.
What happens when the AI gets something wrong?
A response to a complaint misreads the situation, or thanks a guest for something that actually went wrong. Every agent has a defined approval path, and anything sensitive routes to a person before it goes out. Every deployment ships with a documented rollback, so switching an agent off is a decision, not an engineering project.
Do we need a technical team to run this?
No. We build, deploy, and operate the agents. Your side needs one named owner per agent, someone who reviews output and owns the result. That is a role change from generating work to reviewing it, not a new hire.
Will it work with your PMS, Booking.com, or TripAdvisor?
Almost certainly. Orchestration runs on n8n, which connects to effectively anything with an API, and we have built directly against the systems listed above. If a platform has no API, we will tell you that in the audit rather than after the invoice.
Who owns what you build?
You own the output and the data. The agents run on your accounts and your systems. If we stopped working together tomorrow, the workflows and everything they have produced stay with you.
How is this different from just using ChatGPT?
A chat window needs a person to open it, paste context, and copy the answer somewhere useful. That is still manual work with an AI-shaped middle. These agents are triggered by events in your systems, run without being asked, and write their output back where the work actually lives.
Guests can tell when a review response is generic. Does this make that worse?
It makes it better, if you use it properly. A generic reply is what you get when someone answers forty reviews on a Friday afternoon. These responses are drafted against the specific content of each review, and the manager approving them is reading one at a time rather than clearing a backlog.
We are seasonal. Does that break the model?
No, but it changes what you deploy. Seasonal properties tend to lean harder on re-engagement ahead of a season and lighter on continuous monitoring out of it. The agents can be turned down without being turned off.
Ready to elevate the guest experience?
Live in two weeks. No experiments. Measurable ROI from day one.
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