AI Concierge MVP
An AI-powered concierge system for personalized guest experiences
Role
Product + AI Design
0 → 1 MVP
Type
AI Concierge
RAG-powered
Users
Travelers / End Users
AI Stack
LLM, RAG, APIs, Guardrails
The Problem
Completing the travel journey for users required scalable, personalized, and reliable advisory — while unlocking cross-sell opportunities.
Solution: AI Concierge (Scout)
An AI-powered assistant delivering personalized travel advisory across visa guidance and travel advisory.
Core Product Flows
Query Understanding
• Intent detection
• Context extraction
Response Generation
• RAG + API retrieval
• LLM + knowledge base
Trust & Reliability
• Confidence scoring
• Fallback to human agents
AI Architecture
Product Walkthrough
Chat Home
Category-based entry point letting users choose between Sports & Events, Visa Info, Help & Support, or Restaurants & Activities.
Visa Guidance
Structured visa information with expandable sections for documents, processing time, fees, and application tips — powered by RAG.
Visa Details (Expanded)
Drill into specific visa details like fees breakdown, with accurate data retrieved from the knowledge base.
Sports & Events
Real-time fixture data with match details, locations, and dates — demonstrating structured data retrieval capabilities.
Trust & Reliability
Transparent responses to trust-related queries, building user confidence with clear sourcing and credibility signals.
Restaurant Advisory
Personalized restaurant recommendations with ratings, reviews, and highlights — showcasing the advisory experience.
Screenshots from the live product.
Product Thinking
Impact (MVP Stage)
⏱
Reduced dependency on manual ops for repetitive queries
⚡
Improved response speed and consistency
📈
Created foundation for AI-driven advisory at scale
Key Product Decisions
- •RAG over pure LLM responses → improved accuracy
- •Fallback to human → ensured trust in edge cases
- •Structured workflows vs free-form chat → better reliability