AI-Powered Peer Reviewer Identification
A bespoke tool that uses semantic matching and bibliometric profiling to find the most relevant expert reviewers for grant applications — processing hundreds of applications in minutes, not weeks.
identification time
What it does
The Peer Reviewer Tool automates the process of identifying expert reviewers for research grant applications. Given a single application or a spreadsheet of hundreds, it searches across millions of scholarly records and returns ranked shortlists of candidate reviewers — each with a clear explanation of why they were selected.
Each deployment is built around a bespoke knowledge base combining open scholarly data from OpenAlex with a curated dataset of research grants. Clients can enrich this further with their own data — past unsuccessful applications, previous peer reviewer reports, or internal expertise records — making the tool increasingly tailored to their specific funding landscape.
How it works
Input
Upload a grant application, research abstract, or a bulk spreadsheet of applications. The system extracts key concepts, methodologies, and research areas from each submission.
Match & rank
The tool uses semantic embeddings to identify researchers with the closest expertise from the knowledge base, then applies an LLM-powered re-ranking step to assess and explain the quality of each match.
Screen
Potential conflicts of interest are automatically flagged — shared institutional affiliations with applicants, and where unique researcher identifiers are provided, co-authorship history with the applicant team.
Review
Results are delivered through an interactive dashboard — available as a React web application or Power BI — with ranked reviewer candidates, relevant publications, expertise profiles, and conflict flags for each grant.
Proven results
This approach to reviewer identification was first deployed at Alzheimer's Research UK, where it reduced the time research staff spent identifying suitable reviewers from around three hours per grant application to under one hour — a 66% reduction. The tool surfaces a far wider pool of potential reviewers than manual network-based searches, reaching across disciplines and geographies that staff wouldn't typically cover.
“It has revolutionised our processes and upended the way we did peer-review.
Dr Rosa Sancho Chief Operations Officer, MIA Portugal (formerly at Alzheimer's Research UK)
The current tool has been substantially rebuilt since the original ARUK deployment, with a more powerful matching engine and a richer knowledge base. It is now in active use by a major UK health research funder.
By casting a wider net than manual, network-based searches, the tool also supports fairer reviewer selection — reaching across disciplines and geographies that reduce concentration bias. For more on improving equity in peer review and research funding, see our discussion of tackling disparities in research funding.
Who it's for
The Peer Reviewer Tool is designed for any organisation that runs peer-reviewed grant or funding schemes — research funders, learned societies, R&D teams, and institutional research offices. Each deployment is built bespoke — the knowledge base, the dashboard interface, and the reviewer ranking criteria are all configured to match your organisation's processes and policies.
It's available as an ongoing subscription or as a one-off build that's handed over to your team to run independently.
Interested in the Peer Reviewer Tool?
I'd be happy to walk you through a demo and discuss how it could be configured for your organisation.