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International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
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ISSN: 3108-1754 (Online)
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Peer Review: Double Blind
Volume 02, Issue 10

Published on: October 2026

STARTWISE AI: AI-BASED STARTUP IDEA VALIDATION AND FRANCHISE RECOMMENDATION SYSTEM

HAREESH S CHAVAN TEJAS M N NITISH VISHWA S

BHAVYA B P

CSE department VTU University Belagavi ,India

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Plagiarism Passed Peer Reviewed Open Access

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Abstract

Entrepreneurs often face significant challenges in evaluating startup ideas, assessing business feasibility, identifying potential risks, and selecting suitable franchise opportunities due to limited access to structured market information and expert guidance. This paper presents STARTWISE AI, an AI-based decision-support framework designed to assist aspiring entrepreneurs in startup idea validation and personalized franchise recommendation. The proposed framework integrates machine learning, data analytics, and Explainable Artificial Intelligence (XAI) to provide structured insights into early-stage business opportunities.

The startup validation module analyzes user-provided information, including business domain, target audience, estimated investment, geographical location, and business objectives, to support feasibility assessment and identify potential risk factors. Machine learning techniques can be incorporated to estimate business viability, while SHapley Additive exPlanations (SHAP) can be used to interpret model predictions by identifying the relative contributions of input features. In addition, the franchise recommendation module matches user preferences, investment capacity, industry interests, and location requirements with relevant franchise opportunities. The framework is designed using React, Vite, and Tailwind CSS for the frontend, Python and FastAPI for backend services, and Neon PostgreSQL for data storage.

 

 

STARTWISE AI aims to improve the accessibility, interpretability, and organization of preliminary entrepreneurial decision-making. By combining startup assessment with personalized franchise discovery, the framework provides a unified platform for exploring business opportunities. The system is intended to support, rather than replace, professional market research and financial evaluation. Its practical effectiveness must be established through appropriate experiments, comparative evaluation, and user testing.

 

Keywords— Startup Idea Validation, Artificial Intelligence, Machine Learning, Explainable Artificial

Intelligence, SHAP, Franchise Recommendation System, Business Feasibility Analysis, Decision Support System..

How to Cite this Paper

CHAVAN, H. S., N, T. M., NITISH, & S, V. (2026). STARTWISE AI: AI-Based Startup Idea Validation and Franchise Recommendation System. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(10), 1-9. https://doi.org/10.55041/ijcope.v2i10.198

CHAVAN, HAREESH, et al.. "STARTWISE AI: AI-Based Startup Idea Validation and Franchise Recommendation System." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 10, 2026, pp. 1-9. doi:https://doi.org/10.55041/ijcope.v2i10.198.

CHAVAN, HAREESH,TEJAS N, NITISH, and VISHWA S. "STARTWISE AI: AI-Based Startup Idea Validation and Franchise Recommendation System." International Journal of Creative and Open Research in Engineering and Management 02, no. 10 (2026): 1-9. https://doi.org/https://doi.org/10.55041/ijcope.v2i10.198.

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References


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  • •Published on: Oct 28 2026
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