Proof of Usefulness Report

CrowdChem

Analysis completed on 3/20/2026

-25

Proof of Usefulness Score

Lab Mode

While the core concept of applying machine learning to patent data for chemical R&D has strong theoretical utility, the submission is filled with highly suspicious red flags. Claims such as 'most people have used my product' and targeting 'everyone' for a highly niche B2B chemical platform severely damage credibility. Revenue metrics ('all time marketcap: 50000') are nonsensical and active users are left blank. This results in penalizing traction and response quality scores, placing the project well below the zero baseline for verifiable scale.

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Score Breakdown

Real World Utility+100

Audience Reach Impact-50

Technical Innovation+60

Evidence Of Traction-150

Market Timing Relevance+50

Functional Completeness-37.5

Subtotal-27.5

Usefulness Multiplierx0.91

Final Score-25

Project Details

Project URL

crowdchem.net

Description

CrowdChem is a Japanese company based out of Tokyo that combines chemical information from patent documents and a machine-learning model to produce a cross-industry predictive model using neural networks! Our proprietary algorithm analyzes the experimental data to suggest new material combinations, compatibilities, possibilities, and approaches to your challenges and ideas, keeping in mind the desired physicochemical properties. With our teams operating in Japan and the Philippines, we contribute to data-driven research and development through our products, with a goal of bridging the knowledge barrier present between the chemical industry's main players! Feel free to contact us through our LinkedIn page or other avenues listed on our website.

Algorithm Insights

Market Position

Early stage requiring focused development

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