Researchers at leading universities have used Evidano in their published work — and agreed to share how.
Annalisa Raymer
Senior Lecturer & Director of CLASPCornell University
Dr. Raymer uploaded the transcript of an in-house CLASP film into Evidano to summarize four stakeholder groups’ perspectives and run a thematic analysis, then compared the AI’s reading with feedback from adult-education colleagues at the AAACE conference.
“With Evidano, I feel that I have a straightforward thinking partner, rather than an internet pet eager to please.”
Cheng-Ta Wu
Distinguished Professor, College of EducationNational Chengchi University, Taiwan
His team’s published article is itself a case study of Evidano: the authors demonstrate its full qualitative workflow — summaries, themes, codebook, frequency analysis, and key quotes — on elementary-school leadership interview data. They propose a human–AI collaborative model for qualitative research.
“A powerful assistant that not only enhances the efficiency of qualitative data processing but also empowers researchers to concentrate on higher-level interpretation, theory construction, and nuanced analysis.”
Siv M. Gamlem
Professor of EducationVolda University College, Norway
After two researchers completed the initial inductive thematic analysis of 11 interviews, Professor Gamlem’s team ran the anonymised transcripts through Evidano and compared the results with their manual analysis for triangulation and validation.
“Evidano supported our research process by offering an additional lens on the interview data, helping us identify patterns that could be compared with our initial manual analysis. Its value was not in replacing interpretation, but in strengthening the transparency and robustness of our analytic decisions.”
Shawn S. Savage
Assistant ProfessorUniversity of North Carolina Wilmington
After multiple rounds of human coding of narrative student evaluations, Dr. Savage and Dr. Parker used Evidano to interrogate the data from a different analytic vantage point, surfacing gendered comparative distinctions they then verified through collaborative analysis.
“Evidano was most helpful because it encouraged Dr. Parker and me to revisit the data from a different analytic vantage point. It didn’t replace our interpretation; it expanded the kinds of questions we asked.”
Lawrence Meda
Director of Research & Associate ProfessorSharjah Education Academy, UAE
After translating, transcribing, and manually coding nine teacher interviews, Professor Meda’s team used Evidano to categorize participant quotes into researcher-defined themes — with every allocation manually verified by the research team.
“AI-supported tools like Evidano can enhance qualitative research when used carefully and transparently.”
Adriana Cunha Neves
Researcher, Department of Applied ScienceSouth East Technological University, Ireland
Her team used Evidano for AI-assisted thematic analysis of focus group discussions about starch-protein bioplastics, helping mitigate unintentional researcher bias during interpretation.
“Evidano is particularly valuable for researchers who lack extensive experience in qualitative data analysis, offering an efficient way to organize large datasets while minimizing the influence of pre-existing knowledge and researcher bias.”
Munn Hong Lam
Researcher, Faculty of Accountancy and ManagementUniversiti Tunku Abdul Rahman, Malaysia
In a sequential mixed-methods pilot on AI literacy and employment prospects, his team entered the qualitative interview data into Evidano and interpreted it thematically to add depth to their survey results.
“The qualitative element of our research was supported by Evidano through assistance with thematic organisation and interpretation of interview data. This was helpful in our research workflow, particularly in identifying patterns within the responses received during the interviews.”
Evidano is an AI-powered qualitative data analysis platform that helps teams turn interview transcripts into reproducible themes, tagged clinical indicators, and cross-segment comparisons. Fast problem, clear payoff for researchers: the PLOS One phenomenological study (published 29 June 2026) documents lived experiences of depression among 16 women living with HIV in Gondar, Ethiopia, with data collected 25 Aug–25 Sep 2024. Read the original paper at [PLOS One](https://journals.plos.org/plosone/article? id=10.1371/journal.pone.0352678). If you analyse interview transcripts, this post shows how to turn that material into reproducible themes, frequency counts, and cross-segment comparisons using Evidano. Note: this post is research-focused and non-diagnostic.
In this article
Turn lecture and research audio into validated, searchable research assets with privacy-first AI transcription workflows, governance, and a two-week pilot.
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Turn The Washington Post June 28, 2026 feature into reproducible qualitative research on Black graduate unemployment with a 7-step Evidano workflow with tools.
Step-by-step guide to reproduce qualitative analysis of the IPSPC evaluation (25 June 2026), map findings to a Theory of Change, and produce audit-ready outputs with Evidano.
AI-enabled qualitative analysis of wearable data that detects distress early: methods, ethics, and a reproducible workflow you can run in Evidano secure.
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