Proof of Usefulness Report

tuneup.ai

Analysis completed on 2/4/2026

+17
Proof of Usefulness Score
You're In Business

The project 'tuneup.ai' appears to be an academic or early-stage prototype utilizing Deep Reinforcement Learning for computer performance tuning, linked to researchers at East China Normal University and the University of Houston. However, the submission is critically flawed: it makes demonstrably false claims about traction ('most people have used my product'), uses a likely handle ('DeepFang') as the project name, and provides incoherent financial data ('all time marketcap: 500000'). While the underlying technology (Deep RL) shows promise, the lack of verifiable real-world utility, negligible reach, and unprofessional submission quality result in a very low score.

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Score Breakdown

Real World Utility+7.5
Audience Reach Impact+0.5
Technical Innovation+5.25
Evidence Of Traction+0.0
Market Timing Relevance+3.0
Functional Completeness+0.25
Subtotal+16.5
Usefulness Multiplierx1.03
Final Score+17

Project Details

Project URL
Description
TuneUp.ai offers products that use machine learning and Artificial Intelligence to tune up your computer's performance, fully-automated style.

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