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I definitely think there are areas where the platform helps us improve efficiency, in particular for me, I feel like our biggest efficiency gains are in the Single Article Summary (SAS) generation because that is a very time-consuming step for medical writing.

The data summary table and the report outputs, I think, are really a time savings for us because we have a starting point.

The feedback was key in terms of changing the strategies, as well as testing them continuously to see how things could be improved. It was huge. And, thanks to that engagement from the MadeAi team.

I think the feedback is a very critical piece of our engagement. It’s because of the feedback process with MadeAi that we’re able to iterate effectively to understand what needed to improve and then decide on the strategies to overcoming and addressing the issues.

MadeAi-LR dramatically accelerated our literature review process. What typically takes weeks now takes us just a couple of days. Even more impressive, the platform delivers consistently accurate results that our reviewers trust.

With MadeAi, our team cut screening and summarization time in half without sacrificing quality. We’re able to get faster insights, while allowing our team to focus on what to do with the insights rather than the heavy lifting of gathering them.

The platform not only accelerated our literature reviews, but also made downstream reporting significantly easier with structured, ready-to-use summaries.

MadeAi-LR saved us countless hours by summarizing complex articles in seconds—turning an overwhelming review process into a streamlined, manageable workflow.

We were amazed at how accurately the MadeAi platform handled both screening and evidence synthesis. Our reviewers spent less time validating and more time advancing the work.

MadeAi-LR is the most comprehensive end-to-end literature review platform available today.