Grably's AI-Data Platform transforms how individuals share their personal data with AI training providers by creating a user-controlled, transparent marketplace that compensates users fairly while maintaining their privacy and data ownership rights – all within a gamified Telegram app experience that reaches a global audience.
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The Challenge
The AI industry faces a significant challenge with data quality and diversity. Public datasets have reached a ceiling in terms of quality and diversity, while private data collection often lacks transparency, proper consent, and fair compensation. Grably aimed to solve this problem by creating a two-sided marketplace connecting individuals willing to share their data (photos, texts, and other smartphone data) with AI training data providers seeking richer, more diverse datasets.
The platform needed to establish trust with users around sensitive personal data, clearly communicate complex data sharing processes, and create engaging incentive structures to encourage regular participation – all while integrating seamlessly with Telegram's native functionality including its built-in wallet for crypto payments.
Key Challenges
• Creating an experience that felt gamified without sacrificing the app's credibility for handling sensitive data
• Establishing trust through clear privacy policies and terms while maintaining engaging UX
• Designing intuitive task flows that made it clear how users earn rewards
• Balancing technical complexity with accessibility for a mass-market Telegram audience
Process
Stakeholder Collab
• Conducted discovery workshops to align technical requirements with design vision
• Organized regular design reviews to gather feedback on iterations
• Simplified technical jargon from the team into user-friendly language
Project Management
• Created structured timelines for design deliverables
Challenges & Solutions
• Initial requirements contained technical jargon that obscured the user experience
• Resolved by developing a simplified vocabulary that explained the reward process clearly
• Structured task requirements to ensure users understood completion criteria
• Iterated on gamification elements to find the right balance between engagement and professionalism
The Solution
I created a design that balanced gamification elements with trust-building features. Users could discover personalized tasks based on their interests and data sharing preferences, complete these tasks to earn points, and convert these points into cryptocurrencies through Telegram's built-in wallet. To encourage regular engagement, I designed a raffle system that rewarded daily check-ins with bonus prizes.
Key Features
Transparent Data Control
• Clear visualization of what data was being shared and with whom
• Granular permission controls for different types of personal data
Personalized Task Discovery
• Interest-based task recommendations to increase relevance
• Clear indicators of reward potential for each task
Reward System
• Daily check-in incentives through raffle entries
• Points balance with conversion rates to various cryptocurrencies
Impact
Grably successfully launched their platform with a focus on:
• Data ownership giving users 100% control of their data
• User-controlled data sharing for AI modeling
• Fair value distribution for data contributions
Lessons Learned
• Building credibility is paramount when handling sensitive personal data – this must be conveyed through appropriate branding, disclosure, and education
• Maintaining user attention requires focusing on core product value while creating elements of surprise and delight
• Simplifying technical concepts without losing their essence is critical for mass-market adoption