<hi xmlns="http://www.tei-c.org/ns/1.0" style="font-size:11pt">A “distant reading” approach has been taken by Telihuan et al. 2012 and 2014, Perreaux 2021, Leclerq et al. 2021, who study statistical features of larger text corpora extracted from charters. We plan to generalize these approaches with the application of Natural Language Processing (NLP) as a custom, multi-level pipeline. It will resolve information retrieval from both HTR and human-produced data, i.e., address tasks like named entity recognition or relationship extraction, text reuse, and in particular formulaicity detection, but also reflect on the possibilities of named entity linking and text summarisation. We are currently working on laying the basis for this. The wide diversity of dialects and less-resourced languages (early vernacular) is one of the most significant analytic difficulties experienced in medieval and early modern charters. Additionally, the existing OCR of charter texts has insufficient quality for further NLP processing. We show the adoption of a multilingual generic system to tackle both problems by BERT (Devlin et al 2019) models. We create a domain-specific model currently under the pseudonym of “RatisBERT” for OCR post correction, that will be made available through the project’s GitHub repositories. It will be based on human controlled data from Monasterium.net itself, charter corpora like ALIM, CDLM, DEEDS, Glessgen 2016, CAO, and enriched by non-charter specific gold standard corpora like the reference corpora for medieval and early modern German (REM, REF, REN including Rhenish) or the PalaFraFro V2-2. The system takes into consideration a variety of errors originating from HTR and various historical periods and linguistic regions, and provides an effective and automated post-correction approach. We use XLM-RoBERTa for language and variant detection. Through the second layer, the pipeline identifies named entities in the formulaic language of charters, thus forming a solid subset for the abstract generating task, which creates a condensed version of a document in English and other modern languages while preserving its essential information in the standardised format of the charter abstract.</hi>