MuseumSpark: Technical Summary MuseumSpark is an intelligent travel planning platform that transforms the Walker Art Center's reciprocal membership directory into a curated, data-enriched resource for art enthusiasts exploring North American museums. The project combines a React/Vite-based static frontend with a sophisticated Python data enrichment pipeline that aggregates and validates information from multiple sources (Wikidata, Wikipedia, museum websites) to build priority-scored museum recommendations tailored to users' interests and travel constraints. The system implements a multi-phase enrichment architecture (Phases 0–4) currently in Phase 1, with 1,269 museums tracked but only 0.08% fully enriched, demonstrating a methodical approach to data quality. Key features include a comprehensive museum browser with search/filter capabilities, a real-time data quality dashboard tracking enrichment progress, JSON Schema validation for all records, and a "never replace known with null" data governance principle that prioritizes data integrity. The frontend uses modern React 19 with TypeScript, Tailwind CSS, and client-side routing for responsive browsing, while the backend infrastructure leverages Pydantic for validation, BeautifulSoup for web scraping, and a layered pipeline supporting identity verification, metadata extraction, and heuristic fallbacks. The architecture is uniquely designed for iterative enrichment and expert curation, with planned Phase 2 featuring human-driven scoring of collections and Phase 2.5 introducing AI-assisted content analysis via LLM agents to identify signature artists and exhibition patterns. The project targets art-focused travelers and collectors seeking strategic museum itineraries and represents a portfolio piece demonstrating technical solutions in data engineering, full-stack development, and AI integration within a domain-specific application context.