For many broad questions in ecology and conservation biology, the available evidence in the scientific literature is too vast and complex to synthesize using conventional methods. Understanding the global insect decline phenomenon and prioritizing regions and taxa for conservation actions, for example, requires identifying all available datasets documenting long-term insect population and community trends. The entomological literature is enormous, however, and spread across disciplines from agriculture, to human and veterinary medicine, public health, conservation, and ecology. The challenges presented when synthesizing such a vast body of research require new solutions. Here, I present the EntoGEM project--an ongoing effort to systematically map and categorize all studies and datasets documenting insect population and biodiversity trends--to illustrate the challenges of synthesizing evidence for a broad topic and describe solutions developed to support the project: 1) open source software to facilitate identifying studies on nuanced topics, 2) multi-lingual community-driven approaches to synthesis, and 3) text analysis and topic modeling to increase efficiency in article screening for inclusion in the database.