Historiq Una
Historiq Una - a collections workflow tool for archival practice
The Historiq platform powers our processing and digitization services, making delivery fast and consistent. Built with archival standards at its core.
A platform for archival work
A familiar, supercharged approach to arrangement and description
Cataloging and digitization are where collections become usable. But the tools archivists are asked to use often were not designed for archival practice, which makes it harder than it needs to be to capture good description, keep context intact, and move work forward consistently.
We built Historiq to give archivists better tools. The platform supports the way archival work actually happens, helping teams connect description across levels and keep digitized materials tied to their context, so discovery improves without sacrificing rigor.
Connect description across levels
Link box, folder, item, and digital object records while preserving hierarchical relationships and provenance.
Context-aware arrangement
Organize and describe collections in ways that reflect how materials relate to each other, not just linear hierarchies.
Standards-compliant outputs
Export to DACS, EAD, TEI, and other standards while working in a more flexible internal model.
AI metadata drafting
State-of-the-art AI for drafting metadata - optional, governed, and under institutional control
Using AI for metadata drafting is an institutional choice. It can be enabled, scoped to specific tasks, or disabled entirely. All AI outputs are drafts, requiring human review before acceptance.
Handwritten and printed text transcription
Transcribe handwritten and typed materials for review and correction.
Analyze and describe digital materials
Deep analysis of photographs and other digital materials to generate initial description text that archivists refine and approve.
Draft entities, subjects, and dates
AI suggests people, places, organizations, subjects, and dates from context.
Governance: archivist control, review, and traceability
- Granular role-based permissions for archivists, editors, curators, and administrators
- Every AI suggestion and human edit goes through explicit review actions before becoming authoritative
- Publishing workflow ensures nothing becomes authoritative without explicit approval
- Complete audit trail with timestamp, user, and action type for every change and approval
Transparency: models, data, and attribution
Transparency commitments
Model clarity: We are clear about what model(s) are used and where they run. Model information is available in the platform interface.
Attribution: We distinguish model-drafted text and fields from human-authored and approved records.
Data handling: We are explicit about what data is processed, what leaves the environment (if anything), and retention policies. Institutions control their data.
Frequently Asked Questions
Is AI required in Una?
No. Using AI for metadata drafting is an institutional choice. It can be enabled, scoped to specific tasks, or disabled entirely.
Can the platform run offline?
Yes. The platform can be deployed completely offline, even when using AI technologies. On-premises deployments keep all data and processing within your environment.
Built for archival practice
Talk to an archivist about how the platform can improve discovery and description in your institution.