Requirements with a reason.
Check required fields, preserve hierarchy, and surface gaps before publication.
Releasing by November 2026
Turn the material you hold into the archive people find. AI prepares the work. Your people shape the record.
Bring scattered material into one process. Make it readable, reviewable, and ready to reach an audience.
Keep files together with their collection and folder context.
Move between the original, its text, and its description. Inspect suggestions before they become archival decisions.
Shape the requirements, vocabulary, and review process around the collection you actually hold.
Check required fields, preserve hierarchy, and surface gaps before publication.
Review proposed links to people, places, and subjects using your chosen authority sources.
Keep source text and translation side by side, with specialist review where it is needed.
Let automation carry work forward. Give archivists, translators, and rights reviewers clear places to intervene.
Compare the description with the source, correct a date, leave a note, and approve the record for its next review.
See what was suggested, what changed, and who made the decision. Keep the source connected to the description.
“Letter”
Suggestion linked to source material“Relief correspondence”
Title made more descriptiveAccepted for the record
Revision and acceptance remain visibleDemonstration note: “Retain the source wording in the transcription; use the descriptive title for discovery.”
A source, a description, a path into the collection.
Searchable text alongside the original page.
Correspondence in its wider archival context.
Search the records. Follow the hierarchy. Build stories from the sources.
Choose a presentation that serves your audience. Explore three approaches using the same collection materials.
Correspondence, printed records, and the context that connects them.
Explore the collection →Build around the systems your institution uses. Scope the connection, map the fields, and verify the transfer.
Plan an AtoM connection around your descriptive records, collection hierarchy, and destination fields. Mappings and transfer behavior are evaluated during setup.
Archivello brings complex sources, multiple languages, human review, and public access into one connected archival workspace.
A small collection to explore. More capacity as the work grows. A tailored conversation for institutional needs.
Make the first collection count.
A working archive, growing.
Bring the whole team together.
Capacity for larger programs.
Example: a free account has 60 credits left. A baseline page uses one credit in this illustration.
40 credits estimated · 20 would remain.
Custom standards, authority imports, language evaluation, migration, workflows, integrations, and training—scoped to your institution.
Start with collection scope, existing systems, language needs, review roles, and deployment requirements. Subscription and implementation are quoted separately.
Proposed policy: pause new activity that exceeds the allowance and offer a smaller batch or an upgrade. Existing records remain available for viewing, editing, and export.
AI prepares text and descriptive suggestions. Your review process determines which decisions need an archivist, translator, specialist, or rights reviewer.
The proposed model separates described items, storage, and processing credits. A page or image is the baseline unit; complex operations would receive a visible estimate before execution.
Profiles, authority sources, and workflows can be configured to institutional needs. Connector mapping, language performance, and any custom deployment should be evaluated with representative materials.
Start with your collection size, languages, review process, standards, and existing systems. Confirm the plan, access requirements, migration scope, and connector mappings before implementation.