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Proof of Usefulness Report

New Constructs

Analysis completed on 3/23/2026

+358.99
Proof of Usefulness Score
Certified Problem Solver

New Constructs demonstrates exceptional real-world utility with heavily validated proprietary financial data extraction capabilities, highlighted by case studies from Harvard Business School and MIT Sloan. The recent integration with Google Cloud's Vertex AI and Gemini models showcases significant technical innovation. While the company has established strong enterprise traction since 2004 with institutional partners like Interactive Brokers, its overall revenue and direct audience scale remain modest compared to mass-market platforms. The submitted metrics contained exaggerated or vague claims, lowering the response quality score.

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Score Breakdown

Real World Utility+187.5
Audience Reach Impact+40.0
Technical Innovation+72.0
Evidence Of Traction+60.0
Market Timing Relevance+30.0
Functional Completeness+5.0
Subtotal+394.5
Usefulness Multiplierx0.91
Final Score+359

Project Details

Description
New Constructs leverages proven-superior fundamental data (https://bit.ly/381hKF1) to deliver unconflicted insights into the fundamentals and valuation of private and public businesses. Combining human expertise with cutting-edge machine learning (ML) technologies (featured by Harvard Business School: https://hbs.me/308BaTX), the firm shines a light in the dark corners (e.g. footnotes) of hundreds of thousands of corporate financial filings to reveal critical details that drive uniquely comprehensive and independent credit and equity investment ratings, valuation models and research tools. The Journal of Financial Economics (https://bit.ly/3q6G8LI) reveals: 1. Legacy fundamental datasets suffer from significant inaccuracies, omissions and biases. 2. Only our “novel database” enables investors to overcome those flaws and apply reliable (https://bit.ly/303iuoQ) fundamental data in their research. 3. Our proprietary measures of Core Earnings (https://bit.ly/3bQVrD9) and Earnings Distortion (https://bit.ly/3uJkrF3) materially improve stock picking and forecasting of profits. Harvard Business School and MIT Sloan are not the only institutions to write papers on the superiority of our data and research. Find more papers here (https://bit.ly/3uGW0Ih). Now, all investors, not just Wall Street insiders, can access trustworthy research on the earnings and valuation of stocks, bonds, ETFs, and mutual funds. Elite money managers, advisors and institutions have relied (https://bit.ly/3sCT2mj) on us to lower risk and improve performance since 2004. See our client testimonials (https://bit.ly/3dZaa1G) and media coverage (https://bit.ly/3sxYDu2).

Algorithm Insights

Market Position
Strong market validation with clear user adoption patterns
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