Rigorous evidence synthesis, accelerated responsibly with AI — so research can actually reach policy and practice.
Evidence for Impact (evidence4impact.org) is dedicated to leveraging artificial intelligence to assist the knowledge synthesis and implementation process. The site publishes practical, open, browser-based tools for the core stages of a review — study screening, reference verification, data extraction and critical appraisal — alongside plain-language resources explaining how systematic, scoping, rapid and other review types work and why evidence-informed decision-making matters.
Everything published here follows a consistent set of principles: AI proposes, humans decide; methods are documented so results are auditable; named instruments come from published, validated sources; and limitations are reported as candidly as capabilities.
Evidence for Impact is developed by Dr Cong Ngo, an evidence synthesis specialist with extensive experience designing and conducting systematic, scoping, rapid and umbrella reviews for academic, policy and practice audiences.
His expertise spans the full review lifecycle — question formulation and protocol registration, comprehensive search design, dual screening, critical appraisal using Cochrane and JBI instruments, data extraction, meta-analysis and narrative synthesis, and PRISMA 2020 reporting — as well as the knowledge translation work that carries review findings into guidelines, programs and tools.
A single systematic review can involve screening thousands of records, extracting data from dozens of studies and verifying hundreds of references. That mechanical burden is one reason reviews take years while decisions are made in months. Used carefully — with human reviewers in control of every judgement — modern AI can compress that mechanical work dramatically, making rigorous synthesis feasible on realistic timelines and keeping living reviews genuinely alive.