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Extract structured metadata from archival records

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  • Many archival collections still live as paper records: index cards, letters, registers, manuscripts, and records from government and businesses. They are carefully preserved, but you can't search them the way you'd search a database. To find every record that mentions a particular name, place, or date, you'd need to read through the entire collection by hand - a process that could take months or years for a large collection. Even when these records are digitised, the scans remain just images - not searchable data.
  • With AI, you can convert large collections of scanned documents into structured, searchable datasets. Scans are turned into machine-readable text, key fields are extracted, and a search interface lets researchers and staff search across the entire collection - answering in seconds questions that once took months.
  • You remain in control throughout - deciding which data to extract, reviewing output quality, and shaping how the extracted data flows back into your existing catalogues and systems. AI handles the repetitive extraction - your team focuses on quality review, historical context, and expert judgement.
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We collaborate with archives, libraries, and museums across Europe and beyond to push the boundaries of what AI can do for cultural heritage

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From scanned pages to text

OCR and handwriting-recognition tools convert scans of printed and handwritten documents into machine-readable text, creating a foundation for search and analysis across cards, registers, manuscripts and more.

 

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From text to structured data

Next, AI extracts the things that matter – names, dates, places, organisations and keywords – and places them into structured fields. Archivists review and refine these fields in a quality-review dashboard, checking them against the original scans. Once reviewed, the cleaned data is exported into archival information systems or research databases to support ongoing work.

 

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From structured data to discovery

Optionally, we design a search interface tailored to your needs. Staff and researchers can run free-text or fielded searches across the whole dataset, with each result linking back to its original digitised record for context and verification. This makes it much easier to spot patterns and connections across entire collections.

 

Metadata extraction for our clients

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Swiss Federal Archives

Turning 10,000 WWII prisoner-of-war cards into a searchable historical resource.

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Central Archive of the Evangelical Church of the Palatinate

In just a few weeks 1,548 registry cards went from a physical collection to searchable digital records.

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Bielefeld University Library

Using AI to speed up cataloguing of 19th-century children’s books.

Our process in 3 phases

From the initial idea to daily use - we support you with a clear and proven approach. In this way, we ensure that you get exactly the results you need for your work.

Phase 1: Analysis & planning

We start by understanding your collections, constraints and goals, then design a workflow that fits your needs. 

  • Sources: Together we review samples of your collections to understand formats, legibility, languages, existing metadata and structure.
  • Digitisation: If some material isn’t yet digitised, we help you decide how best to do this, either with your own team or trusted partners.

  • Review workflow: Together we agree which fields should be extracted, and how a quality-review dashboard will fit into your existing workflows.

  • Testing: We run a technical test to confirm that the planned approach works.

Phase 2: Pilot project

We run a focused pilot so you can see real results on your own material.
 
  • Pilot dataset: We agree a manageable subset of records that is representative of the wider collection.

  • AI extraction: Scans are prepared and then turned into machine-readable text, and the chosen fields (such as names, dates, places, organisations and keywords) are placed into structured data. 

  • Human review: Your staff review and refine the extracted data in a quality-review dashboard, checking it against the original scans, correcting any errors, and adding information where needed.

  • Evaluation: Together we assess the outcome of the pilot, and ensure the project is ready to scale up.

Phase 3: Scaling up & integration

We scale it up.
 
  • Full collection: We apply the refined workflow to your entire collection, building on what we learned in the pilot.

  • Data delivery: You receive the metadata in the formats you need (for example CSV, Excel or XML), ready for use in your own systems.

  • Search dashboard (optional): Where helpful, we also provide a web search interface so staff and researchers can explore and filter the dataset, with every result linked back to the original digitised record for context and verification.

  • Integration & future use: We support your team as they integrate the new data and tools into existing workflows and explore how the process can be reused for future collections.

Ready to explore this approach for your collections?

Let’s look at your material, your goals, and what kind of results you could realistically expect. A short call is enough to see whether this approach is a good fit for your collections.

Book a free 30‑minute consultation
Gain metadata with Archipanion AI support?

Explore our Case Studies

For collections that are carefully preserved but searchable only item by item, metadata extraction transforms what's possible. Researchers can search across an entire collection - by name, date, place, or theme - and find answers in minutes instead of months. If you're interested in how our clients are using it, explore our case studies.

Explore case studies