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CASE STUDIES
How we summarized thousands of pages of medical information into a microlearning format
CASE STUDIES
How we summarized thousands of pages of medical information into a microlearning format
We deployed LLMs and prompt engineering to extract relevant information from journals, medical conferences, and presentations, delivering summarized insights to our client’s subscribers in under 5 minutes.
We deployed LLMs and prompt engineering to extract relevant information from journals, medical conferences, and presentations, delivering summarized insights to our client’s subscribers in under 5 minutes.
The Client & Category
Our client operates a learning platform that extracts cutting-edge research from top journals and conferences and delivers it in an accessible microlearning format. The platform offers concise, handpicked insights curated by their editors in collaboration with original sources.
The client’s manual content generation process relied on medical writers and physicians sifting through tens of pages to create summaries. This method was time-consuming, costly, and unscalable, highlighting the need for our expertise in automation and innovative solutions.
The Outcome
By implementing Generative AI, our client achieved content summarization in minutes instead of days, reducing their working time by nearly 95%. This optimization allowed them to streamline their team size, strategically deploy personnel to higher-value tasks, and produce content faster.
The Solution
We transitioned the client from manual content creation to an automated AI-based system that understands and highlights relevant medical information for readers.
To keep the client at the forefront of the industry, we leveraged leading solutions such as Open AI, machine learning (SageMaker), and cloud services (Amazon) to achieve the required latency and unparalleled scalability for future growth.