How Cochrane’s Rapid Reviews Methods Group Sets Boundaries for AI Use
On November 24, 2025, the Cochrane Rapid Reviews Methods Group (RRMG) published a position statement in Cochrane Evidence Synthesis and Methods addressing how artificial intelligence should be used in rapid reviews. The statement was prompted by a fast-moving evidence base. A recent evidence map identified nearly 100 studies published since 2021 assessing AI applications in […]
How can we Ensure Responsibility in the Era of AI?
Systematic reviews are among the most trustworthy artifacts in medical research: a structured, reproducible synthesis of everything known about a question, built specifically so that a clinician, a guideline panel, or a regulator can rely on it. But, they’re slow. A single review can take a year or more to complete, and by the time […]
Q3 Product Roadmap – A Letter from the Product Team
Welcome to Nested Knowledge’s first ever prospective product development post! This has been long overdue. Historically, we’ve pushed release notes as they occur, and careful listeners maybe gleaned upcoming features from our videos, blog, and trainings. As usership, product capabilities, and AI possibilities grow, we want researchers to know where NK is headed. Mission Statement […]
AI meets Tagging meets Workbooks with Nested Knowledge’s ‘Index Tables’
If you have reached the end of a systematic review and spent days reformatting extracted data to fit your intended final workbook structure, you already understand the problem Index Tables are designed to solve. Most extraction workflows are built around the act of collecting data rather than the act of using it. The consequence is […]
From Rapid Review to Living Evidence Synthesis
From Rapid Review to Living Evidence Synthesis Why, When, and How to Make the Leap Rapid reviews are workhorses. They get evidence into the hands of decision-makers fast in order to inform early strategic planning, identify evidence gaps, and shape the direction of subsequent research. Increasingly, they also leverage artificial intelligence (AI) to compress timelines […]
From Evidence to Insight — Without Losing the Trail
Introducing Smart Insights: AI-powered synthesis that keeps every claim tied to its source. You Have the Data. Now What? If you work in systematic review, clinical research, medical affairs, or regulatory science, you know this feeling well: you’ve done the hard work. You’ve searched the literature, screened thousands of records, tagged your findings, and extracted […]
Meet Smart Critical Appraisal – Your AI-Powered Bias Reviewer
Stop spending hours manually assessing study quality. Let intelligent automation handle the heavy lifting while allowing you to stay in the loop. In systematic review, critical appraisal is needed for validation, but it’s also one of the most time-consuming steps in the entire workflow. Reviewing every included study for bias, methodological rigor, and quality signals […]
Understanding Deduplication in Nested Knowledge
If you’ve ever uploaded a set of articles into Nested Knowledge and noticed that the numbers shown in your Literature Search, PRISMA diagram, or uploaded files don’t quite match, you’re not alone. Deduplication is a nuanced process, and while Nested Knowledge handles it automatically, there are several key implementation details to ensure deduplication remains sane […]
2025 at Nested Knowledge: A Year of Strategic Growth
2025 at Nested Knowledge: A Year of Strategic Growth As 2025 comes to a close, Nested Knowledge reflects on a year defined not just by growth, but by validation. This was the year our vision for AI-enabled evidence generation moved decisively from promise to proof. At the heart of that progress was a wave of […]
Responsible AI in Evidence Synthesis: How Nested Knowledge Meets the New Standards from Cochrane Joint Statement and RAISE Guidelines
The past year has seen a surge in global attention on the responsible use of AI in systematic reviews. With Cochrane, academic groups, and regulatory-adjacent bodies releasing clearer guidance, including new summaries of the RAISE framework, research organizations are being asked to show exactly how their AI works, how it is evaluated, and where its […]
