Round 1 Winners!
Proof of Usefulness Report

Euclidean Technologies

Analysis completed on 3/17/2026

+77
Proof of Usefulness Score
You're In Business

The submission appears to be a fraudulent or low-effort entry copying the company description of Euclidean Technologies, a legitimate machine learning investment firm. The submitter alias 'BlazeClaw', a suspicious email, and absurd claims such as 'most people have used my product' for a specialized hedge fund strongly indicate a fake submission. Traction, reach, and response quality metrics have been heavily penalized.

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Score Breakdown

Real World Utility+50.0
Audience Reach Impact+0.0
Technical Innovation+22.5
Evidence Of Traction+0.0
Market Timing Relevance+15.0
Functional Completeness+0.0
Subtotal+87.5
Usefulness Multiplierx0.88
Final Score+77

Project Details

Project URL
Description
Based in Seattle Washington, we use machine learning to seek history’s best lessons for evaluating individual companies as potential long-term investments. The lessons we found to be fruitful involve buying good companies when they are offered at very low prices. By embedding these lessons into a systematic investment process, we aspire to protect our investors against unproductive behavioral biases. Our founders John Alberg and Michael Seckler pursued this mission because they had their own money to invest after building a company over a decade and selling it to a Fortune 500 company. The two entrepreneurs wanted an alternative to the short-term focus, risks of leverage, misaligned incentives, and reliance on qualitative analysis that in various combinations accompany many of today’s asset management options. Learn more about Euclidean’s founders and unique investment strategy by visiting our website, and reading our letters to investors.

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