Round 1 Winners!
Proof of Usefulness Report

Scarej

Analysis completed on 3/13/2026

-15.3
Proof of Usefulness Score
Lab Mode

While the project presents a valid concept for AI-driven surveillance, the submission is riddled with severe red flags. Claims such as 'most people have used my product' are demonstrably false. The reported monthly revenue is listed as a 'marketcap' of 500,000, strongly indicating a tokenized asset rather than a legitimate SaaS business with verifiable MRR. The unprofessional responses and complete lack of verifiable traction strictly place this project in the negative scoring tier.

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Score Breakdown

Real World Utility+5
Audience Reach Impact-10
Technical Innovation+1.5
Evidence Of Traction-12.5
Market Timing Relevance+1.5
Functional Completeness-2.5
Subtotal-17
Usefulness Multiplierx0.9
Final Score-15

Project Details

Project URL
Description
a first-of-its-kind AI surveillance SaaS that transforms existing CCTV into a scalable, real-time behavioural intelligence system, capable of detecting aggression and anomalous human behaviour across hundreds of cameras simultaneously. With weapon and trespass detection, <2s alerts, full cloud integration, and no hardware overhaul, we’re redefining what's possible in public safety infrastructure.

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