Proof of Usefulness Report

Audn.ai Inc.

Analysis completed on 3/9/2026

-14.25

Proof of Usefulness Score

Lab Mode

While the project addresses a relevant need in voice AI red teaming, the submission is riddled with severe red flags. The claims regarding traction ('most people have used my product') and audience reach ('everyone') are wildly exaggerated and unsubstantiated. Furthermore, citing an 'all time marketcap' of 500,000 for monthly revenue implies a speculative token model lacking real-world financial metrics. Due to these critical credibility issues and exceptionally low response quality, the project receives a negative evaluation score.

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Score Breakdown

Real World Utility+25

Audience Reach Impact-30

Technical Innovation+7.5

Evidence Of Traction-50

Market Timing Relevance+40

Functional Completeness-5

Subtotal-12.5

Usefulness Multiplierx1.14

Final Score-14

Project Details

Project URL

audn.ai

Description

Audn.AI is an innovative foundational LLM builder company providing red teaming and security services to AI Agents, starting with voice AI agents. Our most breakthrough achievement was developing end-to-end scalable red teaming of Voice AI Agents using our proprietary LLM, Pingu. Pingu is intentionally lobotomized from its security alignments and filters to provide comprehensive security testing. It applies manipulation tactics, exploits known vulnerabilities, and explores undiscovered security weaknesses in AI systems.

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