Round 1 Winners!
Proof of Usefulness Report

Martin & Sorbo

Analysis completed on 3/18/2026

-49.5
Proof of Usefulness Score
Lab Mode

The project identifies a valid B2B use case (ocean freight overbilling detection) but exhibits severe red flags in its submission. Claiming an audience reach of 'everyone' and stating 'most people have used my product' is absurd and contradictory for a niche B2B logistics AI product. The 'monthlyRevenue' is listed as an 'all time marketcap' of 2.5M, suggesting unverified or fabricated metrics. Due to these massive inconsistencies and lack of verifiable traction, the project receives heavy penalties resulting in a negative score, completely in line with calibration guidelines for submissions with red flags.

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Score Breakdown

Real World Utility+125
Audience Reach Impact-50
Technical Innovation+7.5
Evidence Of Traction-125
Market Timing Relevance+10
Functional Completeness-12.5
Subtotal-45
Usefulness Multiplierx1.1
Final Score-49

Project Details

Project URL
Description
We identify major payment and billing errors for our clients. Ocean freight experts train our AI engine to extract every element of an ocean freight invoice. Using state of the art machine learning technology we can claim back whats rightfully the client’s money - 3 years back. With minimal effort from the client we analyze the data and claim back the clients money - a direct bottom line impact.

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