SAIMSARA is a machine-readable medicine and life-science database — independent, human-reviewed, and built as an evidence layer for LLMs, AI agents, and RAG workflows.
Current SAIMSARA database snapshot
Growing evidence layer · updated 2026-05-15
127
SAIMSARA reviews
1,393,262,465
Source study participants
133,919
Source papers
1,054
Source papers / review
Structured evidence your LLM can use immediately
Also available as human-readable science in our Journal
Searches scientific papers and extracts evidence into standardized PRISMA-style scoping reviews,
using major scientific libraries including:
Semantic Scholar — 230M+ papers; retrieves the top 1k matches; best for broad discovery and rare targeted questions.
Europe PMC — 47M+ records; supports full-scale search, including full text where available; best for maximum search depth.
PubMed — 39M+ records; retrieves the top 10k matches; best for precise biomedical and clinical retrieval.
In experimental settings, SAIMSARA has generated reviews with ~20,000 traceable references in ~120 minutes — compressing months of manual literature work into a single session.
Papers assigned to domain-specific issues are checked for clinical integrity, reference quality, and scientific coherence by a World ID verified human editor.
Each issue is paired with its own dedicated AI agent, allowing readers to chat directly with the Journal.
SAIMSARA uses World ID to verify that editorial oversight is submitted by a unique human account.
This adds a proof-of-human editorial layer above the multi-LLM paper-generation workflow and helps
distinguish human-reviewed publications from machine-only outputs.
LLM interface enhanced with direct access to the SAIMSARA scoping review database.
In the Pro version, chat includes access to Deep Panel, a credit-based advanced mode in which Claude 4.6 Sonnet, ChatGPT 5.5, Gemini 3.1 Pro, and Grok 4.3 reason independently before a final judged synthesis is produced by
Claude Opus 4.7.
SAIMSARA Chat can also use openFDA APIs for regulatory drug-label information and medical-device records, including dosage, contraindications, warnings, and indications.
SAIMSARA Chat is intended for scientific and educational use and does not replace professional medical advice.
API access to the SAIMSARA scoping review database, designed to enhance external generative AI systems with independent, large-scale, machine-generated, and human-reviewed medical and life-science information. The Evidence API can be integrated into research, education, clinical-support, or AI/RAG workflows.
API v1 is read-only and does not expose user data. We provide the evidence layer. You build the application.
You remain responsible for its use.
Offline autorun: run long reviews offline and receive the crafted paper by email
Enhanced graphical summaries: richer figures and visual outputs
AI-Native Journal: permanent full-paper unlocks for Pro subscribers
Paper access discount: 30%+ subscriber discount compared with standard temporary paper access
Publishing option: selected papers can be published in the SAIMSARA Journal, ISSN 3054-3991, with optional DOI and named authorship attribution on request
Scientific AI Chat: unlimited chat depth over saved sessions, papers, and issue-level evidence
Deep Panel: credit-based multi-model synthesis for complex scientific questions
Regulatory context: access to openFDA drug-label and medical-device information where available
Evidence API access: read-only structured evidence objects for AI, RAG, education, and research workflows
Export: PDF, TXT, and individual shareable web page URL
Priority support
Free use remains available for limited search, limited chat, and basic export.
Version 4.9 (01.05.2026): Added the ☸️SAIMSARA Evidence API for Pro users, providing read-only programmatic access to structured SAIMSARA evidence objects via authenticated API keys. Active Pro subscriptions include 3,000 requests/month and 60 requests/minute; active week passes include 750 requests/month. API keys remain subscription-bound and automatically stop working when access expires.
Version 4.8 (01.05.2026): Added FDA Medical Device API support to ☸️SAIMSARA Chat, including PMA approvals, 510(k) clearances, UDI/GUDID records, recalls, and MAUDE reports. The router now separates drug-label and medical-device FDA queries; FDA regulatory data remains separate from SAIMSARA literature evidence. EU medical-device regulation may differ.
Version 4.7 (30.04.2026): Integrated the FDA Drug Label API into ☸️SAIMSARA Chat for drug-label questions, with RxNorm/RxNav drug-name normalization and retrieval of regulatory label information on dosage, indications, contraindications, warnings, interactions, and use instructions. FDA label information is shown as regulatory context and does not replace professional medical advice; EU/EMA labeling may differ.
Version 4.6 (26.04.2026): Added World ID proof-of-human verification for ☸️SAIMSARA accounts and Human-verified editorial review badges for editorial layers submitted from verified human accounts.
Version 4.5 (20.04.2026): Added ☸️SAIMSARA Chat as a cross-issue scientific AI agent spanning all journal issues, with integrated Deep Panel for multi-model synthesis across the SAIMSARA evidence ecosystem.
Version 4.2 (12.03.2026): Added citation linkification, separate original and non-original literature synthesis, dedicated Limitations and Conclusion crafting.
Version 4.1 (11.02.2026): Registered ☸️SAIMSARA Journal with ISSN 3054-3991. Updated branding and issue archive (TOC) links.
Version 4.0 (23.01.2026): Integrated Semantic Scholar search, extending SAIMSARA beyond biomedicine to a multidomain corpus (~200M+ papers) across natural and life sciences.
Version 3.8 (06.01.2026): Updated Account UI for Pro users — permanent access and management of saved sessions and crafted papers.
Version 3.7 (23.12.2025): Added PDF export for crafted ☸️SAIMSARA papers (downloadable, shareable paper-style PDF alongside TXT and URL output).
Version 3.6 (19.11.2025): Switched ⛛OSMA to batched processing of input articles for faster evidence bucketing and improved stability. Fixed the head-to-head (H2H) branch, allowing more precise item categorisation in head-to-head comparisons.
Version 3.5 (03.10.2025): Introduced Outcome Sentiment Meta-Analysis (⛛OSMA) — automated evidence bucketing (beneficial, harmful, or neutral for patients or study participants) with sample size ΣN weighting, plus ⛛OSMA Triangle visualizations.
Version 3.0 (13.09.2025): Added automated search in the Pro version — a fully agentic AI-driven workflow from initial search to paper creation. UI improvements: DOI link visualization with embedded metadata preview and an inverted (high-contrast) dark theme. Added visual summary with Figures.
Version 2.5 (10.09.2025): Updated hard keyword filter prior to sending to LLM. Updated Reference logic.
Version 2.0 (03.09.2025): Added Pro version with PMC + PubMed Search.