A Human-Centered Open Source Platform for Image and Text Processing in Humanities Research

We present an open source application designed to support non-technical users in the fields of humanities and social sciences by enabling intuitive processing of visual and textual data. Functioning as an ETL-like pipeline tool, the platform integrates multiple OCR engines and supports the use of large language models (both open source and proprietary) to analyze and enrich image and text datasets. Built with simplicity and openness at its core, the tool fosters accessible, transparent, and reproducible research workflows. This contribution addresses the intersection of AI and Open Science by (1) lowering the technical barrier for deploying LLMs in scholarly analysis, (2) supporting the use of open source models and tools, and (3) encouraging data sharing and methodological transparency. By prioritizing usability and interoperability, the application contributes to training and capacity-building efforts in digital humanities and enhances the responsible adoption of AI technologies within open research infrastructures. The poster will demonstrate real-world use cases, showcase how the platform enables explainable AI workflows for humanistic inquiry, and invite collaboration for extending its modular design.