Government Tourism & Economic Development

Smarter Tourism Investment Decisions with AI-Powered Gap Analysis

Modern Logic built a cost-effective tourism intelligence platform that combines open data, state datasets, AI categorization, and search technology to help Montana identify tourism strengths, gaps, and investment opportunities across communities statewide.

Whitefish Mountain

The Architectecture

A statewide tourism intelligence platform

Our partner, L&S, is one of the Midwest’s most trusted agencies for marketing and web development. When their existing client approached them with a request to build an AI-powered data platform, L&S turned to us, Modern Logic, for help. Our expertise in delivering practical AI for business made this an easy decision.

The ask was ambitious. Build a data platform to catalog tourism assets across an entire State. Do it accurately, but without requiring constant human oversight. Leverage AI advances to make something for a budget that would in years earlier have been unthinkably small.

Our solution? Design a modular, robust architecture. Employ a small, efficient development team to code, review, and deploy, using industry best practices including CI/CD, unit testing, and End-to-End (e2e) integration tests. Bring in open and free data. Iterate on prompting strategies and models to build an efficient, accurate summarization and tagging system that leverages the capabilities of Large Language Models (LLMs). The end result: a searchable, geographically aware (GIS) dataset.

Over 60,000 tourism assets

OpenStreetMap, State data, and DMO integrations

AI categorization, deduplication, and normalization

Balanced gap analysis for rural and urban communities

Automatic and continuous data updates

Long-term use and affordable hosting

A map of a region of Montana showing geographic data

The Challenge

Tourism data scattered across Montana

  • Disconnected datasets

    Tourism-related information existed across inconsistent state, federal, and local sources — none of which talked to each other.

  • Inconsistent records

    The same tourism asset often appeared in multiple systems under different names and categories.

  • Geographic imbalance

    Smaller rural communities risked being overshadowed by larger urban centers in any naive ranking.

  • Tight public-sector budget

    Manual verification and moderation workflows would have exceeded the budget available for a project of this scope.

The Insight

No single dataset could tell the whole story

Montana faced the challenge of understanding tourism opportunities across an enormous and geographically diverse state, where rural fishing towns, ski destinations, and urban tourism centers all contributed differently to the tourism economy.

The real breakthrough came from combining open data, state-managed information, and AI-powered normalization into a unified tourism analysis engine — built to remain practical and cost-effective at statewide scale.

What We Built

An AI-powered tourism intelligence platform

  • Tourism Asset Aggregation Engine

    Collected and unified tourism-related assets from OpenStreetMap, state-managed datasets, and destination marketing organization websites.

  • AI Categorization & Deduplication

    AI models categorize, normalize, and identify duplicate tourism assets across heterogeneous datasets.

  • DMO Website Search Engine

    Indexes hundreds of destination marketing organization websites to discover tourism businesses, attractions, and infrastructure.

  • Balanced Gap Analysis

    Multiple scoring methodologies reduce geographic and population bias when evaluating tourism gaps across the state.

  • Community Self-Representation

    Communities improve their own visibility by updating their websites and contributing directly to OpenStreetMap.

  • Tourism Scoring Visualization

    Visual indicators and scoring models surface tourism opportunity gaps across Montana communities at a glance.

A diagram showing an Amazon Web Services (AWS) Cloud Deployment Kit (CDK) visualization.

Before and After

What changed for Montana

Before After
Tourism information scattered across disconnected datasets and websites Unified statewide tourism intelligence platform
Communities relied on fragmented or inconsistent representation Communities can improve visibility through OpenStreetMap and their own websites
Tourism analysis risked geographic or population bias Multiple balanced scoring methodologies provide nuanced analysis
Tourism planning depended heavily on subjective interpretation Decision-makers have access to measurable statewide tourism data

What Montana Gained

Better decisions. Better data. Better outcomes.

A balanced framework for evaluating tourism

Reduced bias between urban and rural communities

Communities can boost their own visibility

Sustainable, low-cost data maintenance

Practical AI tied to measurable outcomes

Foundation for long-term tourism trend analysis

The Outcome

A platform built for the long term

This project shows a successful collaboration between a state government agency, a partner marketing firm, L&S, and Modern Logic.

Modern Logic delivered a scalable, cost-conscious tourism intelligence platform that gives Montana a more balanced, sustainable way to evaluate tourism infrastructure, identify opportunity gaps, and guide future investment decisions — without relying on expensive, proprietary datasets or heavy manual workflows.

Modern Logic enabled a trusted state partner, L&S, to provide services that might otherwise have been a technical stretch. This strategic collaboration allowed both agencies to play to their strengths to deliver an exceptional outcome.

Frequently Asked Questions

AI can help tourism planning by categorizing and analyzing large datasets, identifying gaps in tourism infrastructure, deduplicating inconsistent records, and generating objective insights for investment decisions.
OpenStreetMap allowed the platform to remain cost-effective, community-driven, and extensible while enabling communities to improve their own tourism visibility directly.
Modern Logic developed multiple scoring methodologies that provide different geographic perspectives, helping avoid overvaluing either large urban centers or smaller rural communities.
AI models were used to categorize tourism assets, normalize inconsistent records, and determine when listings from different systems referred to the same real-world location or business.
Yes. Modern Logic focuses on practical and efficient AI implementations, using the right-sized models and infrastructure for each project while minimizing unnecessary cost and energy consumption.

Bring us your hard problem.

Have fragmented data, operational blind spots, or a difficult planning problem? Modern Logic builds practical AI and custom software solutions designed to solve real business challenges — without unnecessary complexity or cost.