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.”
Researchers and program teams studying Infant and Young Child Feeding (IYCF) interventions need fast, reproducible ways to turn interviews, monitoring logs and diet cards into decision-ready evidence. This post shows how to run a rigorous qualitative analysis of IYCF interventions (using the Palghar tribal block protocol, published 15 July 2026) and how to operationalize the findings with Evidano. You will find a concise study snapshot (n=460 mother–infant dyads), a 7-step workflow for analyzing IDIs, process indicators and WhatsApp logs, and concrete feature mappings to speed synthesis and stakeholder-ready reporting. See the source protocol at [PLoS One](https://www.journals.plos.org/plosone/article? id=10.1371/journal.pone.0353241).
In this article
Turn Palghar IYCF transcripts into actionable themes with an AI-enabled qualitative workflow and an Evidano pilot for coding, visuals and policy-ready briefs.
PLOS One scoping review (July 14, 2026) found seven US studies on Korean immigrant women and alcohol; this guide shows reproducible qualitative workflows and how Evidano scales harmonisation.
7-step workflow to analyze SOUND-BITES hearing interviews, with guidance for using Evidano for transcription, TDF-aligned coding, and cross-segment synthesis.
Evidano guide to SOUND‑BITES qualitative analysis (14 Jul 2026). Use AI to transcribe, code, compare segments, and produce stakeholder-ready reports quickly.
Use AI-enabled qualitative analysis on a PLOS scoping review (July 14, 2026) of alcohol use in Korean immigrant women: key findings (n=7) and a 7-step Evidano workflow.
NTD risk communication in Northern Tanzania (n=57, data May-July 2024): communities frame risk by seasonality; messaging should be timely, trusted, and tailored.
Qualitative analysis of patient expertise: summary of a PLOS ONE study (13 interviews, Jul–Dec 2024) and a practical workflow to scale syntheses with Evidano.
AI-enabled qualitative analysis of Heart of Oregon Corps interviews uncovers themes and visuals; run a 2-week Evidano pilot to produce stakeholder-ready briefs.
Qualitative analysis of the SOUND-BITES hearing pilot: methods, timelines, and AI workflows to turn 600+ interviews into auditable themes for funders.
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