Research Studio is an AI-powered web application designed to revolutionize user experience (UX) research by automating data analysis, thereby saving time and reducing costs. Developed by a team of product designers from Romania, the platform aims to assist smaller businesses with limited UX and marketing budgets by streamlining their research processes. By leveraging large language models (LLMs), Research Studio enables users—including UX designers, product managers, and marketing specialists—to focus on conducting research while the platform handles the analysis, minimizing human bias and accelerating the research cycle. Key Features and Functionality: - Multi-Format Support: Accepts various file types such as PDFs, Word documents, Excel files, and more, supporting over eight formats in 99+ languages. - Instant Summarization: Generates concise summaries of uploaded research documents, providing quick insights into user data. - AI Chat Assistant: Offers an AI-driven chat feature that allows users to ask direct questions about their research data, delivering immediate answers based solely on the provided materials. - Insight Extraction: Automatically identifies key pain points and takeaways from research data, highlighting the top insights without manual intervention. - Persona Generation: Creates detailed user personas from research data in seconds, aiding in understanding target audiences. - User Journey Mapping: Charts customer processes and phases, distinguishing between assumptions and actual user goals. - Data Visualization: Provides AI-generated diagrams that visually represent tasks and processes discussed in research documents. Primary Value and Problem Solved: Research Studio addresses the challenges of time-consuming and costly UX research analysis by automating the process through AI. This automation allows businesses, especially those with limited budgets, to conduct thorough user research without the traditional expenses and time constraints. By reducing research time by nearly two-thirds, the platform enables users to focus on executing research and implementing findings, while minimizing human bias in data analysis.