Axelium vs Universal SLR Assistant

Axelium is an AI-assisted platform for systematic reviews and meta-analyses, spanning evidence search, screening, analysis, reporting, and living reviews. Its 11 stages include protocol, search, screening, full-text review, extraction, RoB 2.0, GRADE, statistics, network meta-analysis, reporting, and living reviews. The maker says AI extracts structured values while deterministic code calculates statistics, and data points link to snippets in original PDFs. Listed methods include pairwise and network synthesis, Cochrane RoB 2.0, GRADE certainty ratings, CERQual, and PRISMA-style reporting. It imports references from tools and databases including EndNote, Zotero, PubMed, ClinicalTrials.gov, and Web of Science; exports include DOCX, XLSX, RIS, BibTeX, and RevMan. Team controls include roles, comments, dual-person sign-off, conflict adjudication, and versioned audit snapshots. A free plan includes one lifetime review and one seat; Researcher costs $29 a month. Human validation is needed for screening suggestions, extracted values, risk-of-bias assessments, and draft reports. Recurring statistical refresh for living-review network meta-analysis is paused, though scheduled cycles can import, screen, and extract new evidence.

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.