Quartex is the only digital collections platform that includes both Optical Character Recognition (OCR) and AI-powered Handwritten Text Recognition (HTR) technology. 

Together, HTR and OCR enable search beyond metadata, making your text-based materials more discoverable and accessible through automated transcription and full-text search. Quartex can become your transcription one-stop-shop; your command centre for generating editable, fully searchable manuscript transcriptions and transcriptions of all your handwritten and printed digital assets.

In-platform transcriptions

Generate highly accurate manuscript transcriptions, with up to 97% character accuracy. Edit transcriptions in-platform or offline for 100% accuracy.

Automated searches

Both HTR and OCR enable text to be identified at document level, with automated searches deployed through the metadata, allowing users to easily navigate between highlighted search results.

Added depth and scope

Displayed alongside the original asset or hidden from public view, automated transcriptions provide an additional data source for site search, extending discoverability and accessibility, and enabling users to add depth and scope to their research and Digital Humanities projects.

Harnessing Handwritten Text Recognition to improve access and discovery across digital collections

The correspondence of Elizabeth Barrett and Robert Browning is presented in The Browning Letters collection by Baylor University Libraries, which has been the subject of a manual transcription programme running over many years. 

The library team is exploring the use of HTR technology in Quartex as part of a project to establish an efficient workflow to deliver accurate transcriptions of these letters.

Optimising access and discovery in an evolving technological landscape

The team at McGill University Library has evaluated the long-term role of HTR Transcription in unlocking the search potential of archival manuscript materials. Watch this webinar to gain a deeper insight into the technology's real-world application and evaluate its role in the development and enhancement of efficient transcription workflows for manuscript collections.

Watch on demand