Proof of Usefulness Report
Crowdception Inc.
Analysis completed on 3/18/2026
+120
Proof of Usefulness Score
Gaining Momentum
The submission targets a meaningful sector (AI in healthcare) but lacks credibility due to exaggerated claims ('most people have used my product') and vague audience definitions ('everyone'). Verifiable traction is absent, and the financial metric provided ('all time marketcap: 2500000') is irregular for a service consultancy.
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Score Breakdown
Real World Utility+50.0
Audience Reach Impact+5.0
Technical Innovation+22.5
Evidence Of Traction+2.5
Market Timing Relevance+60.0
Functional Completeness+1.25
Subtotal+141.25
Usefulness Multiplierx0.85
Final Score+120
Project Details
Project URL
Description
We can help you in configuring, building, deploying and maintaining deep learning models for real-world problems.
Our mission is to apply novel research in machine learning and computer vision to real world problems. We design, develop and provide end-to-end solutions to address these problems. We aim to bring computational intelligence in Medical and Assistive Health Technology to make a significant positive impact on the health of each individual in our society.
Algorithm Insights
Market Position
Growing utility with room for optimization
User Engagement
Documented reach suggests active user community
Technical Stack
Modern tech stack aligned with sponsor technologies
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