Round 1 Winners!
Proof of Usefulness Report

InfiniGraph

Analysis completed on 3/18/2026

-4.25
Proof of Usefulness Score
Lab Mode

InfiniGraph proposes a video recommendation engine using machine learning, but provides zero verifiable evidence of traction despite a 2010 launch date. The submission lacks specific audience metrics and provides vague financial claims alongside absurd hyperbolic statements like 'most people have used my product'. While the core concept of AI-driven video optimization has real-world utility, the egregious lack of evidence, hyperbolic claims, and poor response quality act as severe red flags, placing the project firmly in the sub-zero calibration tier.

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Score Breakdown

Real World Utility+50
Audience Reach Impact-10
Technical Innovation+60
Evidence Of Traction-100
Market Timing Relevance+5
Functional Completeness-10
Subtotal-5
Usefulness Multiplierx0.85
Final Score-4

Project Details

Project URL
Description
About InfiniGraph We help video publishers increase their video lifetime value. InfiniGraph amplifies video play rates through intelligent video recommendation based on what's in the images of the video. Context is KING and leveraging our machine learning technology called KRAKEN™ maximizing your video lifetime value. What It Does... InfiniGraph invented and patented the first video deep learning platform called KRAKEN™ enabling dramatic click to play rates through a learning algorithm that improves over time based on human interactions. The KRAKEN process works over every video type on any network and designed as a mobile first platform. How It Works... InfiniGraph process the big data of video content interaction, billions of images over millions of videos over hundreds of categories. Utilizing machine learning to analysis visuals to best attract consumers and group them enables the best recommendation. KRAKEN learns what resonates with consumers on video and dynamically adjusts to maximizes primary/secondary play and play completion rates. Why It's Valuable... Video is the largest and fastest growing segment in marketing yet there isn't a simple way to increase video lifetime value once a video is published. Consumer visual preferences are powerful for both increasing primary views and secondary views via recommendation. For the industry there are billions being left on the table with un-played video. KRAKEN solves that problem.

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