How should hotels use an AI API?

Key facts

API compatibility	OpenAI-compatible /v1/chat/completions; drop-in base URL change
Models	30+ models behind one API; open-weight options for private deployment
Typical patterns	Reservation Q&A, concierge drafts, ticket summaries, review replies
Integration path	Connects to PMS, CRM, ticketing and review platforms via middleware
Pricing model	Flat monthly self-serve plans with unlimited fair-use usage; no per-token billing — see the live pricing page
Free tier	plugsky-micro and plugsky-lite on the free plan, no card required
Deployment	Plugsky cloud, your VPC, on-prem and air-gapped options
Live endpoints	Chat, streaming, JSON mode, function calling, embeddings, RAG and agents

TL;DR

• Standardise guest answers across properties with versioned prompts.
• Verify policies and rates against source systems, not model memory.
• Keep card data out of prompts and use per-property keys.
• Keep GM approval on review responses and guest-facing drafts.
• Start free with plugsky-micro and plugsky-lite, no card required.

How it works, step by step

1. Pilot one property and one workflow, such as reservation Q&A.
2. Connect policy and rate facts from the PMS or an approved knowledge base.
3. Create a central prompt library with brand-voice examples.
4. Build against the OpenAI-compatible endpoint with per-property keys.
5. Add GM or manager approval for guest-facing output.
6. Measure response time and quality, then expand property by property.

Try it yourself

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Where an AI API fits in hotels

A hotel is a small operation multiplied by many properties. The API should make the brand's best answer the default answer:

• Reservation policy Q&A: answer cancellation, deposit and check-in questions from the property's verified policy.
• Concierge drafts: suggest dining, transport and local options from an approved list for staff to send.
• Review responses: draft replies to guest feedback in brand voice for the GM to approve.
• Maintenance tickets: turn staff reports into structured tickets with location, asset and priority.
• Group-sales drafts: assemble proposals from rate, space and catering data for the sales manager.

Security, privacy and data handling

Hotels handle guest identity, payment and preference data across many systems, so scoped access and verification matter:

• Keep payment card data out of prompts and inside PCI-scoped systems.
• Verify policy and rate answers against the PMS or approved knowledge base.
• Use per-property keys and central prompt versioning so brand rules stay consistent.
• Log guest-facing outputs for quality review and dispute handling.

Deployment options and model choice

A central deployment with per-property keys keeps brand and data boundaries intact across the estate. Deployment is a choice among four tiers on the same OpenAI-compatible API: shared cloud, a private endpoint in your VPC, on-prem and air-gapped, with region selection for residency. The catalogue holds 30+ models behind one key, with open-weight models for disconnected sites, and switching provider is a base URL change. Live today: chat, streaming, JSON mode, function calling, embeddings, RAG and agents. Still coming soon: audio, images, moderation, files, batch, fine-tuning, assistants and the responses API. Start on the free plan with plugsky-micro and plugsky-lite, no card, or use the 14-day full-access trial for paid tiers; the live pricing page has current plans.

From pilot to production

Small-property shortcuts become group-wide problems. Avoid:

• Letting a property edit prompts without review, breaking brand consistency.
• Answering rate questions from model memory instead of the booking system.
• Storing guest data in prompts or logs without a retention decision.
• Automating review replies with no GM approval step.
• Rolling out to all properties at once instead of piloting one.

Pilot one property, connect facts from source systems, and keep a small central team owning prompt versions and brand rules. Measure response time and review sentiment before expanding.

Honest comparison

Capability	Plugsky	Typical per-token API	Building in-house
API compatibility	OpenAI-compatible chat, embeddings and tools	Usually compatible	Full rewrite
Deployment	Cloud, VPC, on-prem and air-gapped	Mostly cloud-only	You operate GPUs and serving
Data residency	Region selection and sovereign options	Limited regions	You control fully
Pricing	Flat monthly self-serve, fair-use usage	Per-token, harder to forecast	GPU plus operations cost
Model choice	30+ models behind one API	Varies by provider	You host every model
Industry fit	Reservation Q&A, concierge drafts, ticket summaries, review replies	Generic API, you adapt it	You build every workflow

Frequently asked questions

Can we keep our existing OpenAI SDK code?

Yes. Plugsky exposes an OpenAI-compatible API, so you change the base URL and model name and keep your integration.

Is there a free plan?

Yes. The free plan includes two free models, plugsky-micro and plugsky-lite, and does not require a credit card.

Can it quote rates?

Only from verified booking data. Ground rate and availability answers with retrieval from source systems so the model never improvises a price.

How does pricing work?

Self-serve plans are flat monthly with unlimited fair-use usage; enterprise agreements cover residency and SLA terms. See the live pricing page for current plans.

Can guest data stay in our region?

Yes. Region-locked planes keep processing in a selected region, with VPC, on-prem and air-gapped options for enterprise setups.

Which endpoints are live today?

Chat completions, streaming, JSON mode, function calling, embeddings, RAG and agents are live. Audio, images, moderation, files, batch, fine-tuning, assistants and the responses API are coming soon.

How do we keep properties consistent?

Own prompts centrally, version them, and require review before changes reach guest-facing surfaces.