Round 1 Winners!
Proof of Usefulness Report

Mathficast Software Services Limited

Analysis completed on 3/12/2026

-23
Proof of Usefulness Score
Lab Mode

The submission presents significant red flags, primarily highly exaggerated claims regarding audience reach ('everyone') and traction ('most people have used my product') which contradict the team size of 6 and lack of external validation. While the market sector of predictive, 'green' AI is timely and relevant, the technical innovation relies on proprietary buzzwords rather than verifiable metrics. Due to unsubstantiated claims and a poor quality submission, the project receives a heavy penalty in the traction category, resulting in a negative score in alignment with the calibration guidelines for projects with red flags.

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Score Breakdown

Real World Utility+12.5
Audience Reach Impact+0
Technical Innovation+7.5
Evidence Of Traction-50
Market Timing Relevance+10
Functional Completeness+0
Subtotal-20
Usefulness Multiplierx1.15
Final Score-23

Project Details

Project URL
Description
At Mathficast Software Services UK Limited Butterfly AI, a new breed of predictive AI as an always-on AIaaS platform live on Google’s GCP, are to solve the biggest challenges faced by world today, including those in healthcare and insurance. Videos: 1. Generative AI? (1:30 min) https://www.youtube.com/watch?v=IMpAq8-bm5E 2. Company Overview (5 min): https://www.youtube.com/watch?v=1iJaCi7zUoo • We provide more ethical AI: Most of today’s predictive AI technologies, when given biased data, generate biased results towards larger classes while missing small anomalies. That may lead to significant problems for example failing to diagnose a cancer at very early stages. Thanks to its disruptive capability called Cellular Balanced Learning Technology©, Butterfly AI avoids bias towards large classes (i.e., simultaneous optimization of accuracy, precision, recall and F1 score). • We provide a greener AI: Butterfly AI doesn’t use neurons or the computationally expensive layers or architecture of today’s predictive Neural Network or Deep Learning, as such it doesn’t require an energy-hungry GPU. As an example, right now, we run it on a four-core CPU. • We provide a human-centric AI: With today’s predictive Deep Learning and AI tech an accuracy metric can’t be used for model training while with Butterfly AI this is now possible by direct embedding of an accuracy optimization threshold to AI layers through its unique Advanced Optimization Threshold Technology ©. • Requires much less data to train unlike today’s predictive AI and Deep Learning technologies. • It is straightforward to prepare the raw data (This will save weeks of work by Data Science and associated costs). • It takes minutes (and with sone large data only couple of hours) to train to achieve +80% accuracy. Today’s AI technology for similar complex prediction problems require much more time. • Ability to self-serve due to MVP platform (Reducing deployment time of today’s AI and Deep Learning by months),

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