Academic papers, studies, and datasets form the backbone of AI training. Stop donating decades of scholarly work to AI companies for free.
From peer-reviewed papers to preprints and original datasets — AI companies are training on all of it. Set your terms now.
Peer-reviewed research, methodologies, and findings. Core training data for AI understanding of academic knowledge across every discipline.
Original research data, statistical analysis, and experimental results. High-value structured knowledge — among the most sought-after inputs for AI training runs.
Academic insights, research summaries, and scholarly commentary. Accessible explanations of complex concepts are heavily used for fine-tuning and RAG pipelines.
Early research findings and cutting-edge developments. Often the first source of new scientific knowledge to enter AI training pipelines — frequently ingested within hours of posting.
Whether you are an individual researcher or managing an entire university repository, implementation is a single line of HTML.
University repositories, research databases, and digital libraries. One tag covers all hosted papers and datasets at any access tier.
Laboratory websites, research group pages, and project documentation. Protect publications, data, and supplemental materials across the entire site.
Individual researcher profiles, personal academic blogs, and CV pages. Higher per-token rates reflect the concentrated expertise of single-author sites.
Decades of scientific knowledge powers AI advancement. It is time researchers got compensated for their contributions.
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