Systematic and scoping reviews as a governed workflow
Capture, screen, code, and analyse in one place, with every decision attributable and every record keeping its provenance from first import to final table.
Industries we serve · Education and research
Research data with its provenance intact.
Research groups, labs, and teaching programmes run on evidence they have to be able to trace: which sources were screened, by whom, against which criteria, and how each finding was coded. Spreadsheets carry none of that, and reviewers and funders increasingly require it.
What we do here
Education and research: the work.
Classification schemes for coding evidence
The scheme your team defines, held as a taxonomy rather than a column header, so coding stays consistent across reviewers and across reviews.
Research data pipelines
DOI and URL capture, bulk import, deduplication, and export to spreadsheets, citation managers, and formatted bibliographies in standard styles.
Analyses that drop into the write-up
Screening funnels, coverage and gap matrices, and the tables a methods section expects, generated from the governed record rather than rebuilt by hand.
How the disciplines apply
The same four disciplines, in this industry.
- Data architecture and standards
- Inclusion criteria and coding schemes as explicit, versioned definitions.
- Systems integration
- Reference sources, screening, coding, and outputs reading one record instead of four copies.
- AI-ready data pipelines
- AI assistance on reading and coding is safe only when every suggestion stays under human review and every record keeps its provenance.
- Custom software
- The tooling researchers needed and could not buy, which is where LitReview came from.
Where a product fits