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 scale coding, quality assurance, and automated scoring. Researchers and UX/clinical teams often ask: can the way patients remember consultations change how well they retain health advice? A July 20, 2026 PLOS ONE study (n=245) shows that recounting perceived validating vs. invalidating consultations raised odds of recalling short health messages by ~19% (and ~22% in the fully randomized subset). This post translates that finding into a reproducible qualitative analysis workflow (from textual recall prompts to coding, QA, and cross-segment comparisons) using AI-enabled tools. If you analyse transcripts, patient narratives, or survey comments, you’ll learn how to replicate the study’s checkpoints (including AI-generated response detection and automated keyword scoring) and how Evidano supports tagging, thematic synthesis, and secure reporting. Note: this article focuses on research methods and is non-diagnostic and research-only.
In this article
AI transcription for qualitative research: transcribe.cpp offers 16+ model families and 60+ variants for private on-device or cloud transcription with Evidano.
Clinician validation increases patient recall (~18.5% higher odds); this post shows an AI-enabled qualitative workflow to scale coding, item-level analysis.
Evidano explains how clinician validation boosts patient recall and how AI qualitative analysis of clinical consultations reveals reproducible insights for care.
Perinatal mental health evidence map for South Asian immigrant women in Canada: AI-enabled qualitative workflow, protocol timeline, checklist, and a 2–4-week pilot.
Practical roadmap to synthesize qualitative evidence on youth digital mental health, reproduce thematic analysis, and run cross-segment pilots using Evidano.
Qualitative scoping of perinatal mental health among South Asian immigrant women in Canada, with a reproducible Evidano workflow to map themes, gaps, and service barriers.
Scale qualitative analysis of youth digital mental health (Nov 2018–Feb 2023 review): AI workflows to ingest studies, run thematic coding, compare subgroups, and visualize evidence.
Reproduce thematic analysis of a 30-interview Thailand mental-health recovery study: methods, themes, and a practical 7-step AI-enabled workflow using Evidano.
Build research-backed user personas using grounded theory, affinity diagrams, and AI-assisted coding; practical UX steps and a workflow to validate minimal personas quickly.
Product updates, research, and tips — straight to your inbox.
© Evidano, All Rights Reserved.
Find exactly what you're looking for