Simplifying Data Access in Public Health with a GenAI-Powered Data Agent​

A global public health organization operating in over 190 countries needed to improve how internal teams accessed structured data. Program officers and regional planners struggled to retrieve insights from relational databases due to their reliance on SQL and technical teams. This slowed down funding decisions, program evaluations, and field-level responses.

Accion Labs engineered a GenAI-powered Data Agent that enabled natural language querying of structured databases while eliminating technical barriers:

• Natural language query processing using LangChain and OpenAI LLMs for accurate intent interpretation
• Vector-based metadata embedding through Chroma for contextual table and column matching
• Multi-stage query pipeline with custom prompt templates and few-shot learning techniques
• Real-time SQL generation across PostgreSQL and Microsoft SQL Server platforms

• Cloud-hosted deployment on Azure for scalability and enterprise security

Business Impact

• Nearly 75% reduction in data access turnaround time
• Improved autonomy for non-technical teams
• Faster program funding and evaluation workflows
• Scalable NLP interface adaptable across departments
  
  

Download the full case study to learn how Accion Labs enabled intelligent, self-service access to structured data, which fueled faster decisions in global public health operations.