Literature Data Extraction
with AI
Define the fields once and extract them across the paper set, each value linked to its source passage.
Pulling study design, populations and outcomes from hundreds of papers by hand is slow and inconsistent.
Define the fields once and extract them across the paper set, each value linked to its source passage.
Structured, source-linked study data ready for reviewer checking.
How DataStruct AI delivers Literature Data Extraction
Evidence-backed AI
Outputs cite the source paragraph. A verification pass flags claims it cannot match to the cited evidence.
Healthcare domain pack
Pre-configured terminology, document types, and rule packs purpose-built for healthcare.
Audit trail by default
Actions are logged and claims link to source. Assemble the evidence without the fire drill.
Access control and audit
Multi-tenant architecture with RBAC and audit logs. Tenant isolation is enforced in the application layer: each tenant-scoped route resolves your workspace membership and permissions before returning anything.
More Healthcare use cases
Systematic Reviews
Extract study data across the paper set with source links; screening and synthesis decisions stay with the review team.
Regulatory Submissions
Rule packs you define for required sections, with source-linked extraction across the dossier for reviewer checking.
Adverse Event Detection
Extraction of reported adverse events with source links; severity is assigned by rules you define.
Run Literature Data Extraction on DataStruct AI
Tell us what you're working with. We'll spin up a tailored workspace and walk your team through it.
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