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 maps study methods to reproducible workflows and accelerates transcription, TDF coding, cross-segment reporting, and QA. Problem: the SOUND‑BITES pilot (published 14 July 2026) embeds hearing checks into Meals on Wheels NSW but relies on mixed qualitative and quantitative data that take months to clean and code. Payoff: this piece shows a repeatable, AI-enabled workflow for qualitative analysis of hearing pilot interviews so researchers, UX teams, and policy analysts can move from audio to action in days, not weeks. We map the study's methods (Arclight otoscopy; Sound Scouts app; n≈60 volunteers, 600 clients/household members; ethics approved 11 Dec 2025; recruitment started 01/03/2026) to concrete workflow steps, from transcription and TDF coding to cross-segment theme frequency and visual reports. Read on to learn the exact imports, auto-coding patterns, QA checks, and deliverables to reproduce SOUND‑BITES qualitative findings fast.
In this article
AI qualitative analysis for the SOUND‑BITES pilot: automate transcription, TDF coding, and cross-segment reporting to turn interviews into stakeholder-ready themes, visuals, and secure audit trails.
AI-enabled workflow to reproduce a July 14, 2026 PLOS scoping review on alcohol use among Korean immigrant women and scale qualitative coding securely.
Playbook for qualitative analysis of AI companions, covering methods, ethics, microcodes, and a secure Evidano workflow for transcription and AI-assisted coding.
Turn Reuters' July 14, 2026 reporting on 59 unpermitted turbines near Southaven, MS into qualitative research findings with a reproducible Evidano workflow.
zra-mcp turns a Zotero library into a local RAG for PDF retrieval, with ONNX INT8 embeddings, bilingual CN↔EN expansion, and LLM-ready evidence blocks for teams.
Turn SOUND-BITES hearing program interviews into reproducible themes using secure transcripts, AI-assisted coding, and cross-segment analysis for stakeholder-ready evidence.
Turn the July 14, 2026 PLOS scoping review into reproducible qualitative insights: AI-enabled methods to map acculturation, religion, and social networks.
Practical guide to qualitative analysis of alcohol use among Korean immigrant women, summarizing a 2026 PLOS scoping review and a reproducible Evidano workflow.
AI qualitative analysis for the SOUND-BITES community pilot: convert interviews, surveys, and clinical notes into rapid, evidence-ready themes and reports.
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