Podnikatelský plán pro AI aplikaci na výživu Gluto

This bachelor’s thesis presents a comprehensive, data-driven business plan for "Gluto," an innovative AI-powered Software-as-a-Service (SaaS) mobile application designed to combat decision fatigue in personalized nutrition. The study aimed to create a theoretically sound and practically viable roadmap for Gluto's market entry and early-stage growth within the European sector, specifically by addressing prevalent user frustrations with existing digital solutions and leveraging modern AI advancements for cost-efficient MVP development. A desk-research methodology was employed, systematically applying established business frameworks such as the Business Model Canvas and Lean Startup principles alongside strategic analyses like PESTLE and Porter's Five Forces. A key component involved a proprietary analysis of over 21,000 competitor app user reviews to identify critical unmet needs. Market sizing for initial launch markets (Germany and France) was conducted using publicly available industry data and benchmarked assumptions, leading to the formulation of an MVP-focused financial plan. The research confirmed a significant market opportunity, underscored by widespread user dissatisfaction with current nutrition apps regarding UI complexity, manual data entry, and opaque pricing. The plan outlines a SaaS subscription model and an initial LTV:CAC ratio of 1.56, with a clear strategy for data-driven optimization towards a sustainable target of >3. This thesis culminates in a practical, actionable roadmap for Gluto, demonstrating the application of rigorous business planning to an AI-SaaS venture. It emphasizes iterative development and validated learning to achieve product-market fit and build a scalable business, offering a pathway to effectively address identified market gaps in personalized nutrition.