AI Services — Foundation
Your systems have APIs. Your AI agents can't reach them yet. That's the gap.
You can already ask an AI assistant a question. What it can't do is check tonight's occupancy in your PMS, pull a patient's latest vitals from your HIS, or query a device's status from your IoT platform — because nobody's built the connection. We build that connection once, using the Model Context Protocol (MCP), an open standard, so it works with every current and future AI agent your team or your guests use — not just one custom integration that breaks the moment something changes.
Before / after
What changes once your systems are AI-reachable
Without an integration layer
- Staff manually check PMS, HIS, and IoT dashboards separately.
- Every new AI tool needs its own custom-built connection.
- Data gets copy-pasted into prompts to make AI useful.
With MCP integration
- An agent queries PMS, HIS, and IoT data directly, in one place.
- One integration layer works with Claude, ChatGPT, or any future agent.
- Staff ask a question in plain language and get a grounded answer.
- Front-desk and reservations staff stop toggling between four systems to answer one guest question.
- A charge nurse can ask “which rooms have had no vitals check in the last 4 hours” instead of scanning a dashboard.
- Facilities teams get device status and maintenance history through the same conversational interface they already use for everything else.
- Your platform becomes reachable by your customers' own AI tools too, if you choose to expose it that way.
How we run it
Assess, build, scale
Integration Blueprint
- System landscape review — mapping which of your PMS, HIS, IoT, ERP, and internal tools are ready to connect, and which need preparation first.
- Architecture blueprint — a documented plan covering tool definitions, data flow, and security boundaries specific to your stack.
- Authentication assessment — how access control and audit logging need to work, especially where patient or payment data is involved.
- Build estimate — a scoped timeline and cost, decision-ready for your management or board.
Custom Integration Server
- Production-ready connection layer built on your existing APIs — no rip-and-replace of your PMS, HIS, or IoT platform.
- Defined tool actions — reading occupancy, pulling patient records within permission scope, checking device telemetry, updating a booking — each scoped and access-controlled individually.
- Authentication and security matched to your requirements, with OAuth support for external or customer-facing access.
- Testing before go-live — validated against real queries before any agent touches production data.
- Deployment and documentation your team can extend without depending on us for every new connection.
Integration Maintenance
- Monitoring so a broken connection is caught before it reaches staff or guests.
- Updates as your systems evolve — a PMS upgrade, a new IoT device type, a changed HIS field — kept in sync automatically.
- New system connections added without rebuilding the whole layer.
- Quarterly access and security audit, with a written report.
FAQ
Common questions
Do we need a new API, or can this work with what we already have?
In almost every case, this sits on top of your existing PMS/HIS/IoT APIs as a translation layer. If your system has a REST API, we can typically build against it directly.
Is this safe for patient data?
Access is scoped per tool action and logged. During the Assess phase we define exactly what an AI agent is and isn't permitted to query or change — a security design decision made up front, not a setting toggled later.
What happens when we add a new property, ward, or IoT device type?
The integration layer is built to extend — new connections get added without rebuilding what's already working, covered under the Scale retainer or as a standalone request.
Can our own customers' AI tools connect to our product this way?
Yes — if you run a booking platform, a patient portal, or a facilities product used by other businesses, this same approach can expose your platform to your customers' AI agents, not just your internal team's.