The project 'Deepnote' (submitted as 'ThunderShade') is a highly established, Series A funded collaborative data science platform with significant verifiable real-world utility and traction (funding from Index/Accel, users at Discord/Gusto). However, the specific submission provided contains extremely low-quality data (e.g., claiming 'most people have used my product', generic descriptions). The evaluation scores the high value of the actual platform based on external verification (Series A status, hundreds of thousands of users) but heavily penalizes the 'Response Quality' and 'Evidence of Traction' quality factors due to the hyperbolic and unsupported claims in the input form.
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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