The submission describes a valid B2B retail technology concept (AisleFire) but is critically undermined by hyperbolic, unverifiable, and contradictory input data. While the core problem (slip/fall safety and shopper analytics) has real-world utility, the claim that 'most people have used my product' is demonstrably false for a specialized B2B solution. Furthermore, the reported financial metric ('market cap: 500000') is incompatible with the claimed team size of 30, suggesting either massive data inaccuracy or a non-viable business structure. The discrepancy between the professional project description and the amateurish input fields ('whosItFor: everyone') results in a minimal score.
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Score Breakdown
Project Details
Algorithm Insights
Recommendations to Increase Usefulness Score
Document User Growth
Provide specific metrics on user acquisition and retention rates
Showcase Revenue Model
Detail sustainable monetization strategy and current revenue streams
Expand Evidence Base
Include testimonials, case studies, and third-party validation
Technical Roadmap
Share development milestones and feature completion timeline