MyRA is an AI platform that accelerates qualitative data analysis for researchers by transforming unstructured text into structured insights. It enables users to upload research materials and ask analytical questions to generate thematic reports and structured datasets, streamlining theme extraction and pattern identification.
Funding
Funding not disclosed
Founders
Product
Problem
Researchers often face significant time constraints when analyzing large volumes of qualitative data, such as interview transcripts and research papers. Manually extracting themes, identifying patterns, and structuring findings into actionable insights is a labor-intensive process that can hinder productivity and delay discovery.
Solution
MyRA provides an applied AI platform designed to accelerate research analysis by transforming unstructured text documents into structured insights. Users can upload various research materials, including interview transcripts and academic papers, and pose specific analytical questions. The platform then processes this data to generate thematic reports or structured datasets, streamlining the analytical workflow. This allows researchers to quickly uncover key themes, identify trends, and derive quantitative insights from qualitative data, thereby enhancing research efficiency and enabling faster discovery.
Target Audience
The primary users are academic researchers, user researchers, students, and analysts who work with qualitative data and require efficient methods for theme extraction and data structuring.
Features
- AI-powered thematic analysis of qualitative data, including interview transcripts and research papers.
- Capability to ingest up to 1,000 files for comprehensive analysis in the MyRA Max package.
- MyRA Quant offers a bespoke data extraction service to transform unstructured text into structured spreadsheets with customizable variables.
- Generates detailed reports including thematic overviews, analysis and implications, and transcript breakdowns with supporting quotes.
- Employs pre- and post-processing techniques to minimize AI hallucination and ensure findings are traceable to source material.
- Data security measures include daily data deletion and a commitment to not training the AI on user data.
- Offers a transparent analytical process, allowing users to verify AI-generated themes against original text.
- Supports both inductive and deductive analysis approaches, enabling cross-checking of findings.