Systematicly vs Universal SLR Assistant

Systematicly is a web-based research platform for systematic reviews, primary research, ethics applications and research proposals. It can analyze a topic using PICO, PECO or SPIDER frameworks and produce Boolean searches for databases including PubMed, Scopus, Web of Science, ERIC and PsycINFO. Reviewers can screen titles and abstracts and upload PDFs for structured field extraction. Analysis options include 1,033 statistical functions, plain-English analysis, meta-analysis, plots, sensitivity analysis and GRADE assessment. The platform lists eight review types, plus publishing tools such as AI-assisted manuscripts and proposals, PRISMA diagrams, journal recommendations and reviewer response letters. It retrieves PDFs automatically from PMC, Unpaywall and EuropePMC, and supports ClinicalTrials.gov imports and several reference formats. The free Explorer plan is limited to three active personal drafts, one lifetime feasibility preview and three lifetime Evidence Answers. Paid one-time options include a single Evidence Answer for $19, paid once and literature review packages from $149, paid once. The security page says user data is not used to train AI models; Anthropic’s commercial API may retain inputs and outputs for up to 30 days for trust and safety monitoring.

Universal SLR Assistant supports systematic and scoping reviews with AI-assisted screening, extraction, and reproducible outputs. It provides a desktop interface and a browser-based local Web App, and imports RIS, BibTeX, CSV, and plain-text references, including exports from PubMed, Scopus, and Web of Science. Its workflow covers abstract screening, full-text PDF processing, structured extraction, and export; likely duplicates are identified by DOI and fuzzy title matching. Workspace mode stores references, PDF metadata, review items, decisions, and audit events in a local SQLite workspace, separating AI suggestions from human decisions. Exports can include decision files and logs, exclusion reasons, PRISMA-ready counts, a methods disclosure draft, and a manifest. The project supports a range of cloud and local AI providers. Cloud providers receive submitted paper text, while Ollama or another local endpoint can keep it on the user's computer or local network. AI results are assistance only: people must verify them and make final review and reporting decisions. The software is free under the MIT License; cloud AI provider API fees may apply.