Moara vs Universal SLR Assistant
Moara
moara.ioUniversal SLR Assistant
sadeghanisi.github.ioSide by side
| Figure | Moara | Universal SLR Assistant |
|---|---|---|
| Price from | $15/mo | Free |
| Free plan | Yes | Yes |
| Free trial | Yes | — |
| Open source | — | Yes |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | — | Yes |
| Plans published | 4 | 1 |
| Spec score · AI Literature Review Software | 8.6 (#4) | 8.2 (#10) |
| API and extensibility | The Teams & Institutions plan advertises custom integrations and APIs, but no public API reference or SDK is identified on the cited pages. | The Web App exposes workspace review and export HTTP endpoints, and contributors can add providers through the LLM interface or OpenAI-compatible profiles. |
| Exports | The product exports formatted bibliographies and supports CSV, BibTeX and RIS exports; cited styles include APA, MLA, Chicago, Vancouver, IEEE and Harvard. | Workspace exports include decision CSV/XLSX files, AI and human decision logs, exclusion reasons, PRISMA-ready counts, a methods draft and a manifest. |
| Privacy | The privacy policy says Moara does not sell personal data or use it for advertising, while allowing service-provider sharing such as AWS hosting and analytics. | The Web App binds to 127.0.0.1 for local use and is not intended as a public multi-user service. |
| Review types | The workflow supports narrative reviews and systematic reviews, including PRISMA and Cochrane-oriented processes. | The software supports systematic and scoping review workflows. |
| Security controls | Moara states that it uses AES-256 encryption at rest, TLS 1.2 or higher in transit, internal role-based access controls and access-pattern monitoring. | API keys are not written to the desktop settings.json or Web App webapp_settings.json, and audit ledgers do not store API keys or full paper text. |
| Support | The product directs users to in-product help icons and support by email at [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 | Moara is a web-based AI research platform for organizing, screening, analyzing and synthesizing literature reviews. | 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
Moara
Moara is a web-based AI research platform for literature reviews, supporting work from discovery through evidence synthesis. Researchers can search, organize, screen, and extract evidence in one workspace, then use its Agent to summarize papers, identify themes and gaps, compare findings, and answer research requests. It supports narrative and systematic reviews, including workflows aligned with PRISMA and Cochrane guidelines. Moara says its database contains more than 200 million scholarly papers across disciplines. Users can import PDFs, RIS, NBIB, TXT, or ZIP files and connect Zotero and LibKey. Teams can assign papers, share annotations, and follow review progress in real time. The Free plan allows up to 50 papers per review library. Core is $15/mo billed annually; Pro is $40/mo billed annually. Moara states that stored data is encrypted with AES-256 and data in transit with TLS 1.2 or higher, with internal access controls and role-based permissions. It says it does not sell personal data or use personal information for advertising.
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.