Round 1 Winners!
Proof of Usefulness Report

AI-Driven Strategic Planning

Analysis completed on 3/22/2026

-34.5
Proof of Usefulness Score
Lab Mode

The submission contains severe red flags, including objectively false claims of traction ('most people have used my product'), nonsensical financial metrics ('all time marketcap: 500000'), and vague, buzzword-heavy descriptions lacking concrete implementation details ('Executive Office' listed as technology). Given the highly unsupported assertions and lack of verifiable data, the project receives a negative score calibration.

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Score Breakdown

Real World Utility+12.5
Audience Reach Impact+0.0
Technical Innovation+7.5
Evidence Of Traction-50.0
Market Timing Relevance+5.0
Functional Completeness-5.0
Subtotal-30
Usefulness Multiplierx1.15
Final Score-34

Project Details

Description
A team of people from Harvard and MIT are working on a project that will use Artificial Intelligence, Robotic Process Analysis, Natural Language Processing, and Machine Learning to automate the strategic planning function performed by most organizations around the world. Our system will be based in the cloud where users will access it 24 hours a day. It will gather, wrangle, and analyze data from 4 domains – resources & competencies, customers & markets, competitors & industries, and external environmental factors. Algorithms will reach conclusions and report them to management. With that foundation, they will make lightning-fast, real-time strategic decisions, yielding competitive advantages. System features will be tailored to each organization. Imagine managers interacting with the system through a combination of a Bloomberg terminal and Spock’s control panel in Star Trek. By deploying this system, users will access much larger volumes of data that are more comprehensive, accurate, and reliable. They will gain greater insights into markets, competitors, and the environment. Managerial bias from choices using instinct, intuition, and experience will be minimized. Strategic decisions will be more timely and up-to-date. Strategic moves will be faster and better informed than the competition. Each system will be designed to the needs and preferences of the individual organization. Amongst its functions, the system will • Scan customer datasets to identify meaningful clusters worth targeting • Identify product feature preferences for both the corporation and its competitors • Use predictive models to forecast future behavior of competitor organizations or individual competitor executives • Use ML to analyze historical trends and project them into the future • Recognize relevant new events or circumstances, correlate them with other existing phenomena, and draw conclusions • Predict historical trends into the future

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