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Research Knowledge and Data Discovery

Research organizations generate papers, datasets, lab notebooks, microscopy, field recordings, and project files across instruments, shared drives, and collaboration platforms. Formats vary by discipline. Sponsored research, consortia, and industry partnerships require strict collaboration boundaries. Unpublished findings and pre-publication data need protection. Literature and internal results live in separate systems. Legacy notebooks and media archives are difficult to search. Export control and IP policies restrict where data can be processed.

Why Traditional Approaches Fail

Discipline-specific tools manage one format well but not cross-format discovery. Institutional repositories handle publications but not linked raw data and lab media. Generic cloud search ignores provenance and collaboration agreements. OCR and transcription are often sent to external APIs, conflicting with sensitive research policies. Public AI tools are unsuitable for unpublished results and licensed third-party content. Dark archives accumulate on storage with no inventory or governance path.

Prodigy unifies publications, datasets, lab notes, and research media under Knowledge Management with provenance and access rules. Enterprise Search spans internal corpora, licensed collections where connected, and project-linked artifacts. OCR and Video Intelligence run on your infrastructure. Dark Data Intelligence helps teams inventory unused archives. Private AI supports summarization and Q&A on governed datasets only. Collaboration boundaries separate sponsor, consortium, and internal work.

Explore Knowledge Management

Security & Governance Considerations

Research data often includes pre-publication results, human subjects constraints, licensed content, and export-controlled material. Prodigy processes and stores content on infrastructure you control. Access policies enforce collaboration and sponsorship boundaries. Audit logs support data stewardship review. Private AI does not send corpora to external training pipelines. OCR and transcription run without mandatory public API calls.

Provenance

Track lineage from raw data to publication.

Collaboration boundaries

Separate sponsor, consortium, and internal access.

On-premises processing

OCR, search, and Private AI inside your perimeter.

Use cases

Example Use Cases

Literature and internal results

Researchers search prior studies, internal reports, and linked datasets for a program without separate repository queries.

Lab notebook digitization

Teams OCR historical notebooks and link entries to current projects and publications.

Instrument and field media

Labs index video and imagery from experiments with timecode and project metadata for review.

Sponsored program boundaries

Administrators enforce access separation between sponsor deliverables, consortium data, and internal work.

Target audience

Who this solution is for

Research directors

Improve discovery without weakening data controls.

Chief scientific officers

Align research infrastructure with IP policy.

Lab informatics managers

Connect instruments, repositories, and search.

Data stewards

Govern provenance, access, and archive inventory.

Sponsored research administrators

Enforce sponsor and consortium data boundaries.

University IT and library leads

Deploy search across publications and research data.

Expected Business Outcomes

Researchers spend less time locating prior work across formats and systems. Data stewards gain inventory visibility into dark archives. Compliance with sponsorship and IP agreements improves when boundaries are enforced in search and access. Lab and IT teams reduce fragmented point solutions for media and document discovery. Unpublished work stays inside approved environments when Private AI is introduced.

Explore research knowledge discovery on your infrastructure

Request a demo to review search, provenance, and governance across your research content types.

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