Project 06 / 15
InfoSysCS
AI-Powered Qualitative Data Analysis Assistant for researchers. Upload interview scripts and receive comprehensive Thematic Analysis reports within minutes using Da-Vinci AI.
Case study / 06
Behind the build
The problem, approach, and impact of InfoSysCS.
- Type
- AI-Powered Qualitative Research Platform
- For
- Qualitative researchers, academic institutions, research consultants and NGO or program teams working with interview data.
01 Challenge
Manually coding and organizing interview transcripts can be time-consuming, making it difficult for research teams to identify recurring themes, extract meaningful insights and produce structured findings efficiently.
02 Approach
Built the Next.js frontend for document upload, authentication, report review and administration, integrating with a separate API for AI-powered document processing and qualitative analysis.
03 Highlights
- Accepts PDF or DOCX transcript uploads and presents AI-generated thematic reports with supporting quotes.
- Provides authenticated report history and a report-sharing workflow for invited researchers and collaborators.
- Uses server-side access checks for protected researcher and administrator pages.
04 Outcome
- Transforms unstructured interview transcripts into organized, AI-assisted qualitative research reports.
- Designed to reduce manual transcript coding and initial thematic analysis effort by automating document processing and theme identification.
Engineering / Technologies
Built with precision.
Technologies and tools powering this project.
- JavaScript
- React
- Next.js
- OpenAI API
- Node.js
Full-Stack Development
AI App Development
SaaS API Integration
Web Application
Web Development