Summary
An AI assistant extracted and synthesized causal evidence from development research to support policy and investment decisions. It standardized and compared results across studies, reducing evidence overload for policymakers and impact investors. By delivering research-backed insights quickly, it enabled more informed allocation of development and impact capital. The approach combined structured data, large language models, and human validation to improve reliability and trust.