Academic SEO is a consultancy that helps biomedical researchers and laboratories improve the discoverability of their published papers and preprints across Google Search, AI retrieval tools, Google Scholar and PubMed.
Academic SEO applies evidence-based optimisation techniques to titles, abstracts, keywords, metadata, and plain-language summaries so research reaches the readers it was written for. Every recommendation is grounded in published research on academic search behaviour and information retrieval, updated for the 2025 AI Overviews era in which more than half of Google clicks never leave the results page.
The work is post-writing, pre-submission discoverability engineering for research papers. Academic SEO operates exclusively in biology and medicine, and treats every manuscript as confidential.
Papers that represent months or years of work go unread because they are not discoverable. The academic publishing system rewards discoverability, yet most researchers receive no training in how search engines, indexing services, or AI retrieval tools surface and rank their work.
Discoverability has changed faster in the last two years than in the previous twenty. Google AI Overviews now intercept the click on a growing share of biomedical queries. ChatGPT, Perplexity, and Claude have become primary entry points for researchers searching for prior work. Google Scholar and PubMed still matter, but they are no longer the only surfaces that decide whether a paper is read.
The flagship deliverable is a structured discoverability audit of a paper or preprint covering title, abstract, keywords, metadata, schema, and AI-retrieval readiness. The audit is evidence-grounded, source-traceable, and written so a working researcher can act on it without further consultation.
Beyond the audit, Academic SEO maintains a body of free content: a guide to the underlying methodology, a grant calendar, a citation hallucination checker, a retraction checker, and a CRediT author statement generator. These tools are free because the underlying problem (research being lost to poor discoverability) is bigger than any one consultancy can solve.
Every cited statistic on this site traces to a public, named source. The site does not publish fabricated datasets, ghost-written "original research", or generic AI-produced explainers. Editorial output is written and reviewed by working researchers, in UK English, with limitations stated honestly alongside claims.
For questions about the audit service, partnership enquiries, or media: gkumar@academicseo.co.uk.
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