QualCoder
ATLAS.ti
MAXQDA
NVivo
Taguette
RQDA
CATMA
Dedoose
Skimle
NVivo
MAXQDA
ATLAS.ti
QualCoder is free, open source software for qualitative data analysis. You can code text, images, audio and video, write journal notes and memos. Categorise codes in a tree-like hierarchical categorisation scheme. Coding for audio and video requires the VLC media player. VLC must be installed for QualCoder to work with audio and video data. Coder comparison reports can be generated for text coding. A graph displaying codes and categories can be generated to visualise the coding hierarchy. Most reports can be exported at html, open document text (ODT) or as plain text files.
Skimle helps researchers, consultants and analysts turn interviews, reports, and other qualitative data into structured, traceable insights. Upload PDFs, documents, audio, video, and more; it transcribes content, extracts themes, and builds a transparent and editable document ร category tables with verbatim quotes and full export capabilities.
Skimle can be used by consultants (e.g., due diligence), market researchers (e.g., group interview analysis), academics (e.g., thematic analysis), public sector (e.g., policy feedback analysis), legal professionals (e.g., litigation discovery) and other knowledge workers wanting to harness responsible AI to improve the depth and speed of their work.
QualCoder SkimleNo features have been listed yet.
Skimle's answer:
Like many others, we got excited by the potential of AI in 2023 and 2024 with the rapid development of LLMs and agentic systems. The hype of magical AI shortly being able to do any task was peaking.
But our personal experiences were painting a different story. Henri was discovering that extracting insights from qualitative data was prone to hallucinations, and even the most sophisticated RAG systems were more akin to search than actual analysis and synthesis of data, and thus useless for many real world applications. Olli was working with agents and AI in large businesses, and saw how few use cases actually worked outside of demos and pilots to provide real impact. Kalle's experience with using AI to speed up customer insight gathering and design was equally disappointing when trying to do anything more complicated.
When helping companies embrace AI and build tools, we discovered the ones that work are based on rigorous expert-designed workflows (not simple LLM wrappers or RAG databases, not broad agents lacking guardrails) combined with keeping the human expert in the driver's seat (not creating AI slop requiring slow manual review and reducing accountability).
Skimle was born in 2025 when the Finnish government wanted a way to reliably assess hundreds of pages of statements to policy proposals. They needed a tool that would be transparent, reliable, rigorous and safe. After developing the first version of Skimle, we realised researchers and academics have equally high standards for a tool to help them in qualitative research. Once Skimle was able to satisfy these two demanding sets of users, we knew it had wider potential. Skimle is built different - combining academic rigour with business applicability. Our unique AI-driven workflow provides more robust answers than simple "AI tools" that are nothing but chat on top of the documents.
With early adopters giving Skimle encouraging feedback, Henri and Olli left their full-time jobs in academia and management consulting, and started working on Skimle full-time in November 2025. Skimle is a start-up based in Helsinki, Finland and funded with private capital as well as Finnish government grants.
Skimle's answer:
Skimle is aimed for experts who need to analyse interview notes, reports, statements, contracts or any other bodies of text to understand common themes. This is a common task for many knowledge workers, and our audiences reflect diverse backgrounds including
I used Qualcoder to code 100 hours of public hearings transcripts and I found it a very pleasant experience. The workflow is intuitive and quick. Even though some transcripts went over 150.000 characters, I was using about 50 codes, and have transcripts with over 100 different coded segments, the program remained stable. Using the | character in the search field allows for the use of multiple keywords at once, which was very effective. The report function allows you to produce overviews of interview segments per code and various kinds of statistical analysis, which can be integrated with R-Studio. Many thanks to Dr. Colin Curtain for the development and software support.
QualCoder is one of the best CAQDAS I have used not just because it is free and open source but also because of the functionalities and constant improvements.
I really like using QualCoder 3.0 for its ease of use and intuitive interface.
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