They needed tools that would foster a culture of seamless, real-time collaboration and empower their workforce to better serve the public.

After a thorough evaluation, Chattanooga selected Google Workspace as the foundation for its transformation. The migration was a resounding success, boosting IT administration productivity by 65% and fundamentally changing how the city operated. This initial success created the confidence and cultural shift necessary for Mayor Tim Kelly to pursue a more ambitious vision: to build a truly data-driven "Smart City."

However, this next phase presented a new, more complex challenge: the city's most valuable data was siloed across dozens of disconnected systems, making a unified view of city operations impossible. To solve this, the city once again turned to Google, trusting the leadership and robust integration of its AI and cloud platform to power the next stage of their strategic vision for a modern, data-driven city.

This unified view allows city leaders to move beyond simple departmental reports and ask complex, cross-functional questions for the first time. By combining these disparate sources, Chattanooga is unlocking a deeper understanding of its operations and paving the way for more equitable and effective governance.

This strategic data foundation is poised to power Chattanooga's first critical initiative: a crash analytics project that aims to transform a once cumbersome, manual process into a dynamic discovery tool. To achieve this, crash data from the state's Titan platform, which was previously pulled into static spreadsheets for hours of manual analysis, is now being piped directly into BigQuery. The objective is to create a constantly refreshed, single source of truth that will help the city make better road safety decisions, faster.

The city is also exploring how Google partner Premier Cloud might help to define the right questions for the analysis. The city is building its solution in Looker to move beyond basic data cuts. At the core of this solution is Looker's semantic layer, which will ensure all analysis is built on a single, trusted source of business logic. By codifying key metrics – like what defines a "high-risk corridor" or "peak traffic hours" – all departments will be able to work from the same reliable calculations, enabling trustworthy self-service analytics.

The vision is to empower analysts to confidently visualize this data on interactive maps and apply dynamic filters to uncover deeper, hidden patterns. The goal is to find the critical insights they "can't see in just the straight up data," with the ultimate aim of allowing the city to make more informed, life-saving decisions, such as:

• Prioritizing which intersections need new traffic signals or redesigned crosswalks.
• Reallocating police patrols to high-risk corridors during specific times of the day.
• Informing long-term city planning and budgeting for road improvements that will have the greatest impact on public safety.

"When we use AI to make our traffic lights more logical, it's like we've added another travel lane to the infrastructure we already have," said Tim Kelly, Mayor, City of Chattanooga. "That's a huge sustainability and quality-of-life win for our residents."

The second initiative tackles the "thicket" of complex city code ordinances, a significant pain point for staff who need fast, accurate answers from dense legal documents. Using Vertex AI , the city has trained a model on its entire municipal code.

While this model is currently in an alpha phase, testing by city staff has already demonstrated its potential. For example, instead of manually searching documents, an employee can ask a natural language question like, "What are the setback requirements for a new deck in a historic district?" and receive a direct, cited answer in seconds – a process that previously took hours.

With plans to deploy the tool internally within the next year, this initiative represents a fundamental shift toward leveraging AI to build a more responsive, efficient, and intelligent government.