AI in Action: Turning complexity into clarity
How we’re using AI to cut costs, boost outcomes, enhance client delivery, and accelerate technical assistance in a fast-changing landscape.
Challenge
A large health agency needed a way to cut through complexity and make sense of the chaos of data from all directions—PDFs, spreadsheets, narrative reports, and evaluation tools. They needed to connect data points, identify insights, and translate it all into relevant information that’s both fast and actionable. Specifically:
- A faster, more efficient way to synthesize information
- The ability to surface themes, patterns, and trends across jurisdictions
- Real-time insights that could inform technical assistance, policy efforts, and more
- The speed to make faster decisions and get the right data to the right people, when they need it
Solution
Working alongside our team of data scientists, developers, health experts, and technical assistance (TA) specialists, we set out to build a smarter approach—one that combined cutting-edge GenAI technology with the critical thinking of human experts: We didn’t just build a GenAI tool. We built a learning system.
Our GenAI platform was built and trained to:
- Start with human context: We began by extracting content from PDF-based work plans and manually developing summaries and themes. These served as training material for the GenAI model, giving it structure, clarity, and a benchmark for quality.
- Train and validate: Our iterative approach meant continuous testing and refinement. Developers and experts worked as a cohesive team to improve accuracy, responsiveness, and consistency.
- Refine and scale: Once validated, the system was used to analyze all submitted plans, quickly identifying patterns across jurisdictions and surfacing findings that could inform strategy.
- Improve access: We designed a user-friendly interface that made results easy to interpret, share, and use for reporting and action.
- Enable predictive analytics: With faster insights and more thorough analysis, staff were able to dedicate more time to data visualization, reporting, and planning.
“What used to take months, we now do in hours.”
Outcomes
By integrating GenAI into our TA approach we were able to bring meaningful change to the way a large-scale health agency approached program data. The client gained:
- Better, faster decisions: AI-enabled insights helped teams act more quickly, with greater confidence.
- More time for critical tasks: With the time saved, teams now have the capacity to surface needs through other mechanisms (project officer calls, TA events, etc.) and enable more timely and relevant TA delivery. We’re able to identify who needs help with what and get them the right help much sooner than before.
- Smarter resource allocation: Patterns and trends pointed to where support was needed most. We’re now able to use the resources saved to create value-adds like dynamic dashboards that are available to our whole client team (not just our COR or technical monitor).
- Improved outcomes: Faster feedback led to more responsive planning, helping jurisdictions strengthen their public health efforts.
Together, these gains have had measurable, positive impacts on the agency’s mission, supporting speed, efficiency, and accuracy—making a difference that can be seen and felt. This model is now helping 90 state, local, and territorial health departments (and their partners) across two funded opportunities improve mission delivery—giving them clarity when and where it counts.