International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | IdeaSense: AI-Driven Framework for Startup Idea Assessment and Validation |
|---|---|
| ABSTRACT | The journey from an idea to a successful startup is fraught with uncertainty, and inadequate validation remains one of the primary causes of early-stage failure. This research introduces IdeaSense, an AI-driven framework designed to assess startup ideas through a structured, data-supported evaluation process. The system employs natural language processing, market trend analysis, competitive landscape mapping, and scoring algorithms to evaluate idea originality, market demand, competition, revenue potential, and technical feasibility. It integrates multiple data sources to generate real-time validation reports and SWOT analyses. The study highlights the architecture, operational flow, and practical implications of such a system for early-stage entrepreneurs, academic incubators, and students. By providing intelligent and accessible decision support, IdeaSense seeks to reduce failure risks and promote data-driven innovation. |
| AUTHOR | ALVIN RAM CHANDRA PRAJAPATI, DR.D.WILLIAM ALBERT |
| PUBLICATION DATE | 2025-10-18 |
| VOLUME | 175 |
| DOI | DOI:10.15680/IJIRCCE.2025.1310013 |
| pdf/13_IdeaSense AI-Driven Framework for Startup.pdf | |
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