Round 1 Winners!
Proof of Usefulness Report

Qen Labs Inc.

Analysis completed on 3/17/2026

+161.5
Proof of Usefulness Score
Gaining Momentum

The project operates in a highly technical and promising domain (spatiotemporal ML for physical systems in defense & space), which yields a decent technical innovation and market relevance score. However, the submission relies on severely vague, hyperbolic, and unverified claims (e.g., audience reach of 'everyone', traction stating 'most people have used my product', and ambiguous revenue described as 'all time marketcap: 2500000'). Due to the lack of credible evidence and poor response quality, the project's quality multipliers are heavily penalized, resulting in a low final score.

Ready to Compete for $150k+ in Prizes?

Move this data into a HackerNoon blog draft to become eligible for your share of $150k+ in cash and software prizes

View All Reports

Score Breakdown

Real World Utility+50
Audience Reach Impact+10
Technical Innovation+45
Evidence Of Traction+12.5
Market Timing Relevance+50
Functional Completeness+2.5
Subtotal+170
Usefulness Multiplierx0.95
Final Score+162

Project Details

Project URL
Description
An AI research commercialization company building machine learning models for physical systems using spatiotemporal data. We believe in the power of open business models to create positive-sum outcomes for everyone.

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