What it is
The platform scans stored literature to identify topics that lack an updated systematic review, then generates targeted search strategies and retrieves candidate studies across multiple databases.
Records are cleaned, deduplicated, and screened, and the engine produces structured systematic review drafts in which every claim is linked back to its source. As new evidence appears, the review can be regenerated and kept current.
How it works
- 01Research question parsing
- 02PICOS-based input
- 03Synonym and search strategy expansion
- 04Multi-database retrieval
- 05Metadata standardization
- 06AI screening model
- 07Structured review drafting
- 08PRISMA-style output
- 09Continuous update monitoring
What sets it apart
Feature 01
End-to-end review automation
Feature 02
Dynamic review updating
Feature 03
Citation-linked claims
Feature 04
Multi-model screening consensus
Feature 05
Editable document output
Where it applies
From concept to clinic
Search engine prototype
Screening model validation
Review drafting module
PRISMA export
Academy-wide research platform