Round 1 Winners!
Proof of Usefulness Report

LLMfeed

Analysis completed on 3/22/2026

+97
Proof of Usefulness Score
You're In Business

The project submission for LLMfeed lacks verifiable evidence and relies on vague, unrealistic claims (e.g., 'most people have used my product', 'everyone' as the target audience). Technical details are extremely limited, with 'Internet' listed as the sole technology used, indicating a highly speculative or nascent project. The overall lack of substantiation, coupled with unclear traction metrics, results in a low score consistent with minimal verifiable real-world impact.

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Score Breakdown

Real World Utility+25.0
Audience Reach Impact+5.0
Technical Innovation+45.0
Evidence Of Traction+2.5
Market Timing Relevance+40.0
Functional Completeness+1.25
Subtotal+118.75
Usefulness Multiplierx0.82
Final Score+97

Project Details

Project URL
Description
LLMfeed is an AI-native platform combining an autonomous content engine with an ML/LLM crypto trading bot. Founded by master’s student Roman Di Domizio, we’re building a bot that generates data-driven, backtested on-chain signals using trained machine-learning models and refined large language models, alongside a pipeline that publishes concise market updates across social channels. Built on the We Own AI decentralized infrastructure.

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