Archival Backlog Reduction with AI-Powered Text Recognition

2,000+

Archives and libraries

200M+

Pages processed

300+

Public AI models

250+

Cooperative members

The problem

The Hidden Collections Crisis: Archive Digitization Backlogs Keep Growing

OCLC estimates that more than 30% of archival collections in the United States alone remain "hidden" — unprocessed, uncatalogued, and effectively invisible to researchers. The situation is comparable across Europe and beyond. These are not marginal materials. They include correspondence, legal records, administrative files, and manuscripts that researchers cannot discover because no finding aid, catalogue entry, or searchable text exists for them. Every year the backlog grows as new acquisitions arrive faster than understaffed teams can process them.

Staff shortages are structural, not temporary — archives cannot hire their way out of the backlog

Manual transcription of a single archival box can take weeks of skilled labour

Unprocessed collections generate no citations, no research, and no public engagement

Grant-funded digitisation projects often cover imaging but not text recognition or metadata creation

Mixed collections — typescript, handwriting, printed forms — require different approaches that slow manual workflows further

Unprocessed archival boxes awaiting cataloguing and digitisation

The solution

Reduce Archival Backlog with AI: From Unprocessed Boxes to Searchable Records

Transkribus enables archives to process collections at a scale that manual workflows cannot achieve. Upload scanned images — entire boxes, series, or fonds — and run AI text recognition across thousands of pages in a single batch. The platform's handwritten text recognition (HTR) handles the scripts and document types most common in archival holdings: administrative handwriting, official correspondence, court records, municipal registers, and mixed-format files. The result is machine-readable, searchable text that can be exported directly into archival information systems.

Batch processing: queue thousands of pages and process them unattended — no page-by-page intervention

300+ public AI models trained on historical scripts from the 15th century onward

Export to PAGE XML, ALTO XML, and TEI-XML for ingest into ArchivesSpace, AtoM, and other systems

Metagrapho API enables fully automated pipelines for mass digitisation workflows

Publish processed collections directly as searchable digital editions via Transkribus Sites

Transkribus for archives

Transkribus batch processing interface for large-scale archival collections

How to process an archival collection in 4 steps

Upload scanned collections

Upload entire series or fonds as multi-page PDFs, TIFFs, or image batches. Transkribus handles layout detection — columns, tables, marginalia — automatically.

Select an AI model

Choose from 300+ public models filtered by language, century, and script type. For mixed collections, run multiple models on different document groups within the same project.

Run batch recognition

Queue thousands of pages for processing. Transkribus runs text recognition in the background — no manual intervention required. Monitor progress from the dashboard.

Export and integrate

Export results as PAGE XML, ALTO XML, TEI-XML, plain text, or searchable PDF. Ingest directly into ArchivesSpace, AtoM, or publish via Transkribus Sites.

At scale

Automated Archival Processing with the Metagrapho API

For institutions running large-scale or recurring digitisation programmes, the Metagrapho REST API enables fully automated processing pipelines. Integrate text recognition directly into your existing imaging and cataloguing workflows — no manual uploads, no browser-based interaction. The API supports model selection, batch job management, and structured output retrieval, making it suitable for production-grade mass digitisation projects.

REST API with full documentation for integration into institutional workflows

Programmatic model selection — choose different models for different collection types automatically

Structured JSON output with text, coordinates, and confidence scores for each text region

Batch job management: submit, monitor, and retrieve results for thousands of pages

Combine with entity recognition to extract names, dates, and places for catalogue enrichment

Metagrapho API for batch processing

Metagrapho API documentation for automated archival processing

Frequently Asked Questions

Ready to address your archival backlog?

Speak with our team about institutional plans for large-scale collection processing, or create a free account to evaluate Transkribus on your own materials.

Talk to us Start for free

Used by 2,000+ archives and libraries worldwide

200M+Pages processed

2,000+Archives and libraries

300+Public AI models