Aims, scope, and publishing model

SAIMSARA Journal is an experimental project created to address the rapid growth of scientific evidence in medicine and life sciences and the limitations of human-written reviews and meta-analyses. Articles are generated by an AI RAG workflow that searches and extracts literature from three major libraries: Semantic Scholar (~230M papers), Europe PMC (~45M papers), and PubMed (~39M papers).

Each review follows a PRISMA-style screening workflow and includes outcome-oriented synthesis (beneficial, harmful, or no clear effect), weighted by study sample size. References are transparent and traceable. Issues then curate domain collections and power a dedicated AI RAG chatbot for interactive Q&A on the issue topic.

Articles are released Online First. Each registered SAIMSARA user can publish a generated article from their account. Published articles are reviewed by the Editor-in-Chief and curated into topic-specific domain issues. Each issue powers an interactive AI RAG chatbot that everyone can use for Q&A.

SAIMSARA Journal publishes machine-generated syntheses with human editorial oversight. The goal is reproducibility, traceability, and rapid updating.

Institutional and library access is available on request. Libraries, universities, hospitals, and research organizations may request custom access to all published SAIMSARA papers, including full human-readable articles and machine-readable Evidence JSON objects, under individual conditions.

Institutional paper access is separate from the Pro synthesis workflow and does not include unlimited AI paper generation unless separately agreed.

For conditions, pricing, and activation details, see Institutional access.

Need a SAIMSARA review on a specific topic? Individual standardized scoping reviews can be created on request and adapted to the preferred scientific context, such as clinical, educational, research, or AI/RAG-oriented use.

Custom reviews may include editorial check-up and can be prepared as a human-readable paper, machine-readable Evidence JSON object, or both. To request a custom topic, contact info@saimsara.com.