For Academic & Scientific Research
AI for Academic & Scientific Research
Who it is for
- Universities
- Research institutes
- Grant-funded labs
- Think tanks
- Academic publishers
Build institutional knowledge that compounds
Problem and approach
Where academic teams lose time today
- Decades of research papers sit in repositories but are unsearchable at depth
- Cross-departmental knowledge sharing is limited to personal networks
- Thematic analysis across large corpora requires months of manual reading
- New researchers spend months understanding the state of existing work
- Grant proposal literature reviews are repetitive and slow
What DataStruct does
- Corpus-wide semantic search across all institutional publications
- Automated thematic clustering and topic extraction
- Cross-paper evidence synthesis with citation tracking
- Cross-paper search with source-linked passages
- Grant literature sections started from source-linked extraction
Use cases
Academic use cases
Literature Review Acceleration
PhD students and postdocs spend 6-12 months on literature reviews.
Field extraction across papers with source links; screening and synthesis decisions stay with the researcher.
Institutional Knowledge Layer
University research output is scattered across departments and unsearchable.
Unified semantic search across institutional repository with role-based access.
Grant Proposal Acceleration
Grant writing requires deep literature reviews repeatedly across funding rounds.
Search and extraction across prior reviews so literature sections start from source-linked evidence.
Systematic Reviews
Cochrane-grade reviews take teams of researchers 6-18 months.
Field extraction across papers with source links; screening and quality assessment remain reviewer decisions.
Documents and questions
What academic teams bring, and ask
Documents it reads
- Journal Articles
- Theses
- Working Papers
- Conference Papers
- Grant Applications
- Peer Reviews
- Book Chapters
- Preprints
Questions you can ask
- “What are the main findings in this paper?”
- “Compare methodologies across these studies”
- “What gaps in the literature are identified?”
- “Summarise the theoretical framework”
- “Identify key themes across this corpus”
How findings read
The same evidence model in every sector
Answers cite the sources they rely on. Records DataStruct could not confirm are shown separately for a reviewer to check, related material is kept apart from evidence, and a finding with no support says so. Access is controlled by workspace roles, and sensitive actions are audit logged.