Proof of Usefulness Report

TrueRisk Labs

Analysis completed on 3/23/2026

+19.8

Proof of Usefulness Score

You're In Business

The submission describes a valid B2B financial machine learning use case but severely undermines its credibility with exaggerated, highly implausible claims regarding traction and audience reach ('everyone', 'most people have used my product'). The 'all time marketcap' metric is anomalous for standard monthly revenue. As a result, quality multipliers are heavily penalized for vague and unsupported claims, leading to a minimal overall score.

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Score Breakdown

Real World Utility+7.5

Audience Reach Impact+2.0

Technical Innovation+9.0

Evidence Of Traction+1.25

Market Timing Relevance+2.5

Functional Completeness+0.25

Subtotal+22.5

Usefulness Multiplierx0.88

Final Score+20

Project Details

Project URL

truerisklabs.com

Description

TrueRisk Labs is a securities markets research and technology firm. It applies machine-learning engines to new data sources to generate forward-looking sentiment and risk metrics that enhance existing portfolio strategies. It can also help to create entirely new strategies. Our data is suitable for all portfolio management disciplines, whether wholly or partly discretionary, quantitative, or systematic. Our research data forecast security-level returns and volatility more accurately, compared with empirical and/ or price-driven risk/ return models.

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