Structured AI platformengineered for scalable learning
UI/ux design for a dating platform
system design for AI-driven education
Client
Cray
Industry
Other
Headquarters
United Kingdom
Services
UI/UX Design
About project
Cray is an AI-driven platform designed to create meaningful digital connections through intelligent matching, structured interaction patterns, and behavior-aware recommendation systems.
Human-Readable Translation
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We engineered a hardware-compatible interface that translates confusing crypto actions into clean, readable experiences.
Existing platforms prioritized volume over quality — shallow matching algorithms and cluttered interfaces led to low meaningful engagement and high churn.
Zylo engineered a behavioral matching engine and intentional UX design that reduced cognitive load, guided users toward meaningful interactions, and improved session depth.
Process
Discovery
Behavioral analysis
User journey mapping
Engagement metric review
Competitive analysis
Churn driver identification
Product Architecture
Recommendation engine design
UX pattern library
Interaction flow structure
Notification system logic
Analytics integration
Implementation
Frontend engineering
Algorithm tuning
A/B testing setup
Launch optimization
System Architecture
The recommendation engine uses behavioral signal processing, preference modeling, and real-time engagement scoring to surface high-quality matches.
Interface Engineering
The interface was intentionally stripped of distractions — clean profiles, structured conversation starters, and progressive disclosure of features maintain user focus.
Technology that connects people through intention, not just proximity.
MOBILE-FIRST
EXECUTION
Mobile-first interaction patterns were designed around natural thumb zones, swipe ergonomics, and notification timing optimized for user retention.
UI Kit
Component library covers profile cards, match indicators, conversation threads, interest tags, and engagement score visualizations.
AUTOMATION
FRAMEWORK
Match scoring, compatibility weighting, notification triggers, and engagement nudges are fully automated through the behavioral intelligence layer.
Design system
Results
Measurable outcomes from real-world AI and engineering deployments.
+83%
Improvement in meaningful match rate
2.6×
Increase in average session depth
-47%
Reduction in 7-day churn rate
4.7/5
App store rating post-redesign
Verified across 500+ enterprise deployments
Let's work together
3-day AI Engineering Collaboration
Sprint
AI-driven collaboration sprint with senior engineers to design, build, and refine real-world software solutions. Focused on execution, technical depth, AI capability, and product thinking—not just ideas, but working systems.