Proof of Usefulness Report

Buluttan

Analysis completed on 2/2/2026

+217
Proof of Usefulness Score
Gaining Momentum

Buluttan is a legitimate weather intelligence startup utilizing NWP and Deep Neural Networks, a high-utility approach in the current climate tech market. However, the submission quality is exceptionally poor, featuring hyperbolic claims ('most people have used my product') and missing financial data. While external verification confirms the company's existence and regional B2B traction (likely in Turkey/Energy sector), the score is significantly penalized by the lack of direct evidence provided and the low effort of the response. The project falls into the 'Small but promising' category due to strong technical fundamentals despite the weak presentation.

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Score Breakdown

Real World Utility+85.00
Audience Reach Impact+16.00
Technical Innovation+48.00
Evidence Of Traction+20.00
Market Timing Relevance+36.00
Functional Completeness+2.00
Subtotal+207
Usefulness Multiplierx1.05
Final Score+217

Project Details

Description
We combine Numerical Weather Prediction (NWP) and Deep Neural Networks (DNNs) to build the state of the art architecture for weather forecasting. We build weather intelligence around our stakeholders to enhance operations, safeguard assets and protect people with precision.

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