ReviQ vs Universal SLR Assistant
ReviQ
github.comUniversal SLR Assistant
sadeghanisi.github.ioSide by side
| Figure | ReviQ | Universal SLR Assistant |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | Yes |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | — | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 0 | 1 |
| Spec score · Systematic Review Software | 6.7 (#28) | 8.2 (#6) |
| Intended users | The project describes its workflow for researchers conducting systematic or multivocal literature reviews, including reviews with up to five reviewers. | It is intended for PhD students, researchers, professors, evidence synthesis teams, and systematic or scoping review authors. |
| Purpose | ReviQ is a locally deployed workbench for systematic and multivocal literature reviews. | Universal SLR Assistant supports systematic and scoping review workflows with AI-assisted screening, extraction, and reproducible outputs. |
| Review workflow | It supports eight phases, from project setup and importing references through screening, quality assessment, data extraction, and results. | The workflow covers reference import, abstract screening, full-text PDF processing, structured extraction, and export. |
Plans
In their own words
Universal SLR Assistant
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.