Proof of Usefulness Report

Social-I Networks Ltd.

Analysis completed on 3/8/2026

+165
Proof of Usefulness Score
Gaining Momentum

Social-I Networks Ltd is a legitimate UK-based consultancy specializing in 'Social Intelligence Networks' and data science for healthcare/EU projects, founded by Dr. Hamza Zeytinoğlu. While the entity and its academic underpinnings are verifiable and valuable (B2G/B2B context), the submission itself suffers from severe quality issues, including demonstrably false claims of 'everyone' as the audience and 'most people' as users. The 'marketcap: 500000' figure likely refers to cumulative project funding or revenue (~£500k) rather than valuation. The project is a credible niche service provider but lacks the mass-market traction claimed.

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Score Breakdown

Real World Utility+63.00
Audience Reach Impact+8.00
Technical Innovation+39.00
Evidence Of Traction+27.00
Market Timing Relevance+28.00
Functional Completeness+2.00
Subtotal+167
Usefulness Multiplierx0.99
Final Score+165

Project Details

Project URL
social-i.co
Description
Bringing data science to socially networked endeavors centered on values driven personal and organizational improvement, development and transformation for healthy and sustainable societies Social-i is a spin-off from previous EU projects especially around its Social Intelligence Networks platform and its backend data science services, with the goal to bridge the gaps between human values and relevant actions individually and collectively. Social-i products and services include customizable digital platforms; data science services based on AI/ ML; applications for change management and social and healthcare innovations/ social impact projects and consulting and mentoring services. The goal is to bring multi-disciplinary applications from various areas into implementations in healthcare services delivery, digital and public health. Social-i is the country partner of ValueMatch™ for Turkey and Azerbaijan for Spiral Dynamics Integral values assessment tools and localized training.

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