About Us

Literature reviews are essential for evidence-based decision-making, but even with the exponentially increasing amount of evidence, they no longer need to be cumbersome.

Founded in 2021 to support urgent COVID-19 research, PICO Portal was built to help researchers conduct literature reviews with greater accuracy and efficiency. Developed by a team of experts from the fields of AI technology and Evidence-Based Practice, PICO Portal is used by 10,000+ researchers in 100+ countries, has supported the review of more than 10 million records, and is cited in the methods of 130+ published studies.

Leadership Team

From policy-making and guideline development to R&D and regulatory reporting, we support researchers across government, academia, non-profits, and private sectors. With a philosophy to provide safe and transparent AI, PICO Portal provides robust, customizable literature review technology alongside expert methodology services, ensuring researchers stay in full control while accelerating their work.

Services

Beyond Just a Research Tool

AI Research Revolution

Offering a new kind of platform to transform literature reviews, our technologists and evidence-based practitioners leveraged expertise in advanced document analysis, artificial intelligence, and evidence synthesis to create a solution that streamlines the review process.
Advanced Evidence Automation

Our comprehensive evidence synthesis platform offers a modern user interface, flexible workflows, and intelligently improves the review process with priority screening, keyword highlights, and AI-assisted quality assessment and data extraction.
Expert Review Support

When you're short on resources, our expert literature review services will enable your team to complete your review on-time and within budget. Our global network of methodologists seamlessly plug into your project when and where you need.

Services

Leadership Team

Eitan Agai, M.Sc.

Founder and CEO
Karen A. Robinson, M.Sc., Ph.D.

Chief Scientific Officer / Director, Johns Hopkins University Evidence-based Practice Center and Professor of Medicine, Epidemiology and Health Policy and Management
Riaz Qureshi, M.Sc., Ph.D.

Senior Methodologist / Assistant Professor, Department of Epidemiology; Ophthalmology at University of Colorado Anschutz
Renee Wilson, M.S.

Senior Methodologist / Senior Research Associate, Department of Public Health Policy and Management at Johns Hopkins University
Juleen Lam, Ph.D., M.H.S., M.S.

Senior Methodologist / Associate Professor, Department of Public Health at California State University, East Bay
Mary Butler, Ph.D., MBA

Senior Advisor / Co-Director, Minnesota University Evidence-based Practice Center and Associate Professor, Division of Health Policy and Management

About us

Trusted by Top Researchers

“Using AI prediction we identified 95% to 99% of all of eligible citations by screening fewer than 10% of our initial citations. We’re all used to the standard of two people having to independently screen every citation. Do we need to rethink that?“
“We had 15 committee members at 15 different institutions that all needed to help with this review. We identified 5,172 references and the AI showed likely includes before likely excludes. That helped us get the literature out to the community sooner.”
“The value for us was the tagging function. It was just a matter of adding a couple of clicks of the mouse and we were able to watch the distribution of literature across this wide range and approach it as evidence ecology. We looked at the full range of research designs from RCTs to qualitative research.”