Designing an evaluation under time pressure
3ie needed to evaluate a complex intervention that had evolved over more than a decade, on a constrained timeline. The evidence included evaluation reports, administrative databases, policy documents and briefs, ministry websites, and other institutional records, along with in-person workshops and individual consultations with stakeholders.
The article is written by five 3ie researchers and data scientists. It sets this example alongside three other AI applications: image classification, outcome extraction from documents, and digitizing handwritten records.
Where Evidano fit
The team used natural language processing to analyze more than 500 pages of program documents. For the stakeholder engagement, Evidano supported translation of audio recordings from Spanish to English, transcription from audio to text, and discussion summaries across nearly 20 interactions.
Together, the document analysis and the consultation summaries allowed the team to develop a rigorous, contextually grounded evaluation design within a compressed timeline.
Quality checks
The authors stress that AI output demands at least as much rigor as any other method. Across the projects described, teams reviewed all AI-generated transcriptions and summaries to make sure intent was accurately conveyed.
They also note that large language models are not deterministic, so errors must be identified, quantified, and corrected, much like measurement error or inter-rater differences in traditional evaluation.
Why this case matters
This case shows Evidano at the front end of an impact evaluation, turning multilingual stakeholder consultations into usable English transcripts and summaries quickly enough to shape the evaluation design.
For evaluators working across languages and tight timelines, it is a practical example of AI expanding what is feasible while human review keeps the results trustworthy.
Limits and responsible interpretation
The source is a practitioner article rather than a peer-reviewed study or full evaluation report, and the intervention is not named. Evidano is one of several AI tools described, and its role covered translation, transcription, and summarization rather than full thematic coding.
How Evidano fit the workflow
- 1Gather the documentary record
Reports, databases, policy documents, and websites covering more than a decade.
- 2Analyze documents with NLP
More than 500 pages were structured and interpreted.
- 3Consult stakeholders
Workshops and individual consultations were recorded in Spanish.
- 4Translate, transcribe, summarize in Evidano
Audio was translated to English, transcribed, and summarized across nearly 20 interactions.
- 5Review every output
All AI-generated transcriptions and summaries were reviewed to ensure intent was accurately conveyed.
- 6Design the evaluation
Documents and consultations together informed a contextually grounded design.
“An AI-enabled qualitative analysis platform (AILYZE) supported the translation of audio recordings from Spanish to English, transcription from audio to text, and generated discussion summaries across nearly 20 interactions.”
Spanish recordings became English transcripts and summaries.
Consultation insights arrived within a compressed timeline.
All transcriptions and summaries were checked for accuracy of intent.
3ie names Evidano in its published account of AI use.