AI for genealogy: how to extract data from old documents
Baptism records from the 19th century, parish registers in Latin, handwritten immigration lists — thousands of such documents exist in digitized archives. Artificial intelligence has begun to make data extraction from these documents feasible at scale. But real possibilities come with real limitations.
What AI can extract from genealogical documents
AI-based extraction tools can identify structured fields in historical documents even when the text is not printed — as long as the scan quality is reasonable and the document type is recognized.
| Extracted field | Example | Note |
|---|---|---|
| Registered name | Person A Parent A | Surname matched against known variant database |
| Event date | March 14, 1872 | Written-out dates or Roman numerals |
| Event location | São Leopoldo Parish, RS | Locality and parish when legible |
| Event type | Baptism / Marriage / Death | Automatic classification by text pattern |
| Father | Parent A | |
| Mother | Cônjuge ExampleSurname | |
| Godparents / Witnesses | Godparent A and Godparent B | Role in event detected by context |
| Entry number | Entry no. 47, fol. 12v | When present in the document |
How AI-powered extraction works
The process starts with optical character recognition (OCR) of the document image. For printed documents, conventional OCR produces sufficiently good text. For manuscripts in old cursive handwriting — especially Kurrent — computer vision models such as Gemini are better suited.
After OCR, the AI extraction engine looks for patterns typical of the document type: which field comes before and after a name, which words indicate kinship, which structures indicate dates. The output is a structured record with separated fields.
KinProof performs this extraction for genealogical documents in bulk: the researcher uploads a PDF, selects the target surnames, and the platform returns structured records with events, persons and inferred family relationships.
Important limitations
- ⚠AI does not authenticate documents and does not replace analysis by a qualified genealogist.
- ⚠Heavily damaged documents, those with extensive staining, or scans below 150 DPI tend to produce incomplete extraction.
- ⚠Rare names, unusual spellings or little-known localities may not be recognized correctly.
- ⚠Kurrent script (19th-century German cursive) has a higher error rate than documents in standard Latin script.
- ⚠Records in Latin may have mispositioned fields if the document structure is atypical.
- ⚠Results should always be reviewed by the researcher before being used as genealogical evidence.
When to review manually
Manual review is always recommended, but it is especially important in the following cases:
- Dates with Roman numerals or unusual abbreviations (e.g. "XIV Kal. Apr.")
- Names with superscripts, strikethroughs or corrections made by the priest
- Documents with multiple entries per page where the boundary between records is unclear
- Highly irregular handwriting or excessive flourishes
- Documents partially illegible due to physical damage, moisture or fading
- Any field that will be used in a legal process (citizenship by descent, inheritance)
Document types that work best
AI-based extraction works best when the document has a predictable structure and reasonable scan quality:
- Parish baptism records (17th–20th century) — standardized structure with well-defined fields
- Civil birth, marriage and death certificates
- Immigration and naturalization books — lists with tabulated fields
- German, Italian and Portuguese parish records — strong results with KinProof
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