Delve

QCAmap is an open access web application for systematic text analysis in scientific projects based on the techniques of qualitative content analysis. QCAmap can be used within research projects in e.g. psychology, sociology, education, economics, linguistic sciences, to analyze small and large amounts of any text material and images coming from interviews, group discussions, observation protocols, documents, open-ended questionnaire items and others. Qualitative Content Analysis is a strictly rule-guided procedure containing qualitative steps (assignment of categories to text passages and images) and quantitative steps (analysis of category frequencies). We have developed a web-based interactive software package, which leads you step by step through the different techniques of Qualitative Content Analysis. The software is free available. All your old projects are migrated to the new version and can be used as normal.

Skimle transforms unstructured qualitative data into structured, analyzable datasets using AI. Unlike RAG chatbots that retrieve random passages, Skimle systematically processes entire document sets upfront—analyzing each section, extracting insights, and organizing them into hierarchical theme taxonomies. Upload interview transcripts, PDFs, audio/video, reports, or any qualitative data. Skimle's worklow (inspired by academic thematic analysis) codes every passage, identifies patterns, and creates a "spreadsheet" where documents are rows and themes are columns. Every insight links to verified quotes - no hallucinations. 100+ languages, 1,000+ docs/project, GDPR-compliant EU storage, full traceability (themes↔quotes), editable categories, AI reasoning chat, export to Word/Excel/PowerPoint reports etc. Why different: Combines academic-grade rigor with AI speed. What takes weeks in NVivo or other legacy tools takes hours in Skimle, with full audit trails for peer review.