Purpose-Built AI for Hospitality
Agentic architecture anchored in your property's specific knowledge base, designed to securely automate operations while keeping you in complete control.
How every message turns into action.
Guest messages stream in from any channel. The agent reasons, retrieves context, and executes across your stack in milliseconds.
Traditional Chatbot
- ✕Static decision trees and rule-based scripts
- ✕Generic answers lacking property-specific details
- ✕Dead-ends when guests ask complex or multi-part questions
RigoMind Platform
- Multi-LLM routing based on query complexity
- Property-specific RAG (Guest Profiles, KBs, Inventory)
- Autonomous multi-step tool execution (booking, billing, etc.)
Intelligent Model Routing
We run a multi-LLM architecture. Queries are dynamically routed based on intent, optimizing for latency, cost, and reasoning capability.
| Query Type | Engine Tier | Median Latency | Notes |
|---|---|---|---|
| FAQ & retrieval | Lightweight (8B-class) | ~800ms | Open-weight model available for clients with stricter data-handling requirements |
| Complex reasoning | Frontier reasoning | ~2.5s | Multi-step planning and cross-system tool execution |
| Sentiment / tone | Custom fine-tune | ~400ms | Domain-tuned on hospitality dialogue |
| Intent classification | Encoder model | ~50ms | Ultra-low latency ingress filtering |
- Stateful Context WindowMaintains continuity across multi-turn, multi-day guest journeys without losing context.
- Agentic Task ExecutionAutonomously decomposes complex requests into multi-step action plans.
- Advanced NLU PipelineNatural Language Understanding that sharply distinguishes between informational FAQs and actionable intents.
* Measured internally across rigorous evals on property data (hallucination defined as non-factual response or policy violation).
# Live Tool-Call Trace
guest_query = "Is the spa open? My back is killing me, room 302."
tools.search_kb(query="spa hours") # 120ms
tools.get_guest(room="302") # 85ms
tools.analyze_sentiment() # Urgency: High (Back pain)
# proposed action: book_service(massage, 7pm)
# tools.book_service deferred until confirmation
return "The spa is open until 9 PM. Since you mentioned back pain, I can book you a deep tissue massage for 7 PM. Shall I confirm?"
19:41:22 [INFO] intent_classified: spa_booking (conf: 0.98)
19:41:23 [WARN] action_deferred: book_service requires user_auth
19:42:05 [INFO] tool_executed: agent.book_service · room 302 · approved by guest
19:42:06 [INFO] trace_id: req_9f8a2b1 · status: success
Latency & Reliability
Technical buyers care about performance at scale. Industry research suggests chat abandonment increases sharply past 3 seconds, so we architect for speed.
Concierge Reply Budget
p50: 1.8s · p95: 3.2s
Edge Infrastructure
We co-locate the agent control plane with regional model endpoints and PMS connectors to keep tool-call round-trips under 200ms.
System Telemetry
Failure Mode Handoff
If reasoning confidence drops below 0.7, or if a tool API fails, the agent immediately hands off to human staff with full conversation context and error traces.
Safety & Control Boundaries
We know hospitality buyers worry about runaway agents. You have explicit, granular control over when the AI handles a request and when it escalates to a human.
- User-controlled AI boundaries
- Programmable escalation triggers based on VIP status, sentiment, or monetary value
- Comprehensive audit log of every reasoning step and tool call
Security & Compliance
Transparent status on enterprise security and privacy requirements.
| Standard / Control | Status | Notes |
|---|---|---|
| Data Encryption | Done | AES-256 at rest, TLS 1.3 in transit. |
| SOC 2 Type II | Audit in Progress | SOC 2-aligned controls implemented. Audit target Q3. |
| GDPR / CCPA | Supported | Data Subject Rights workflows available. DPA on file. |
| Data Residency | Roadmap | EU/India regional data pinning planned for Q4. |
See it run on your data.
Go beyond marketing claims. Bring a sample guest inquiry and let our engineering team show you how the agent reasons, retrieves, and resolves.