Case Study: Juisci saves 100 hours by automating text synthesis with Lettria

How Juisci saved 100 hours by automating large volumes of text synthesis

Juisci, a company that provides a mobile app for healthcare professionals to access and summarize scientific publications, faced the challenge of manually processing an overwhelming volume of new medical research. The manual synthesis of complex, lengthy papers was extremely time-consuming. To automate this, they partnered with Lettria to implement an NLP solution.

Lettria developed an API that automatically analyzes and synthesizes dozens of pages of text into concise, sub-15-line summaries. The solution proved to be 200 times faster than manual processing, saving an estimated 100 hours of work for every 100 papers analyzed. The automated summaries were also found to be of identical or better quality than handwritten ones, leading to high user satisfaction and enabling Juisci to scale its operations.

Juisci