Sysrev vs Universal SLR Assistant
Sysrev
sysrev.comUniversal SLR Assistant
sadeghanisi.github.ioSide by side
| Figure | Sysrev | Universal SLR Assistant |
|---|---|---|
| Price from | $50/mo | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | Yes |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 4 | 1 |
| Spec score · Systematic Review Software | 8.4 (#4) | 8.2 (#6) |
| Spec score · AI Literature Review Software | 8.4 (#7) | 8.2 (#10) |
| Exports | Project data can be exported as EndNote XML, Excel workbooks, Parquet files and bundled PDFs. | Workspace exports include decision CSV/XLSX files, AI and human decision logs, exclusion reasons, PRISMA-ready counts, a methods draft and a manifest. |
| Intended users | The maker describes Sysrev as suitable for researchers conducting systematic, scoping, and rapid reviews, including collaborative institutional teams. | It is intended for PhD students, researchers, professors, evidence synthesis teams, and systematic or scoping review authors. |
| Purpose | Sysrev is a platform for data curation and systematic evidence review. | Universal SLR Assistant supports systematic and scoping review workflows with AI-assisted screening, extraction, and reproducible outputs. |
| Support | Users can submit an in-project issue report or email [email protected]. | The project directs users to the Complete User Guide, in-app Help panel, output logs, tests, and GitHub issues for support. |
| What it does | Sysrev is a web application for collaborative and automated document review and structured data extraction. | Universal SLR Assistant helps researchers import references, deduplicate records, screen literature, process PDFs, extract structured data and export auditable review outputs. |
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.