Proof of Usefulness Report

QAT Global

Analysis completed on 3/24/2026

+11

Proof of Usefulness Score

You're In Business

The submission exhibits significant red flags and logical inconsistencies. The project claims to be a 'start-up' but lists a launch date of 1995, provides nonsensical financial metrics ('all time marketcap' instead of monthly revenue), and makes highly improbable assertions ('most people have used my product', reach is 'everyone'). The description relies on verbatim generalized statements from McKinsey and Harvard Business Review rather than detailing a specific product or custom technology. Consequently, all criteria receive the lowest quality multiplier (0.5) due to vague, unsupported, and contradictory claims.

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Score Breakdown

Real World Utility+4.0

Audience Reach Impact+1.0

Technical Innovation+1.5

Evidence Of Traction+1.0

Market Timing Relevance+2.0

Functional Completeness+0.5

Subtotal+10

Usefulness Multiplierx1.1

Final Score+11

Project Details

Project URL

qat.com

Description

QAT is a start-up tech company specializing in digital computing services, AI Marketing and web services. According to Harvard Business Review, marketing’s core activities, such as understanding customer needs, matching them to products and services, and persuading people to buy, can be dramatically enhanced by AI. A 2018 McKinsey analysis of more than 400 advanced use cases showed that marketing was the domain where AI would contribute the greatest value. The ability to leverage AI can not only help automate and streamline processes but also deliver personalized, engaging content to customers. It enhances the ability of marketers to target the right audience, predict consumer behavior, and provide personalized customer experiences. AI allows marketers to process and interpret massive amounts of data, converting it into actionable insights and strategies, thereby redefining the way businesses interact with customers. At QAT we're your AI Marketing companion into the future. AI Tools Machine Learning Deep Learning Generative AI Large Language Models CRM Tools

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