About Peronaite UX
Our Vision
Peronaite UX revolutionizes user experience testing by creating an AI-powered focus group environment that provides rapid, insightful feedback on UI designs without the need for actual users. By harnessing the power of AI-generated personas, we enable designers and developers to iterate quickly and confidently.
Our name "Peronaite" derives from the ancient Greek concept meaning "the right, critical, or opportune moment" - perfectly capturing our mission to provide UX insights at exactly the right time in the design process.
Why Peronaite UX?
- ✓ Get UX insights in minutes, not days
- ✓ Test with diverse AI personas at any time
- ✓ Receive structured, quantifiable feedback
- ✓ Identify usability issues early in the design process
- ✓ Reduce costs and time-to-market
Problem We Solve
Traditional UX Testing Challenges
- ➤ Time-consuming recruitment of test participants
- ➤ High costs for focus groups and usability studies
- ➤ Scheduling difficulties with real users
- ➤ Limited diversity in test participants
- ➤ Difficulty in early-stage testing before full implementation
Peronaite UX Solutions
- ➤ Instant access to AI-powered personas
- ➤ Cost-effective alternative to traditional testing
- ➤ 24/7 availability for testing iterations
- ➤ Diverse persona generation with customizable characteristics
- ➤ Testing from concept designs to final implementation
Reduction in testing setup time
Lower cost than traditional focus groups
More design iterations tested
Increase in detected usability issues
"Waiting for traditional user testing often causes designers to skip vital feedback loops. Peronaite UX's AI-powered approach enables continuous design improvement with immediate feedback, fundamentally changing how we approach user interface development."
- Promising UX Researchers
How It Works
Define Personas
Select characteristics or upload research to extract diverse user profiles
Upload Design
Upload your interface design image for AI analysis and element detection
AI Evaluation
LLMs analyze the design through the lens of each persona(inferred details by LLM), generating comprehensive feedback
Review Results
Explore visualizations, heatmaps, and detailed feedback from different personas
Iterate Design
Apply insights to improve your design and repeat the process for continuous refinement
Detailed Workflow Breakdown
1. Define User Personas
Create realistic user personas using three methods:
- Select from predefined characteristics (age, technical skills, goals, etc.)
- Upload your user research documents for AI extraction
- Start with base personas and let AI enhance them with realistic traits
2. Upload UI Design
Our system processes your UI design through several steps:
- UI element detection identifies interactive and static components
- OCR extracts text content for context understanding
- Component relationship analysis maps user flows
- Automatic interface annotation for focused feedback
3. AI Evaluation
Each persona interacts with your design through AI simulations:
- Persona-specific testing categories (usability, accessibility, etc.)
- Structured questions generated based on UI elements
- Multi-dimensional analysis across different user journeys
- Likert scale responses and detailed explanations
4. Review Results
Comprehensive visualization and analysis tools:
- Interactive heatmaps show problematic UI areas
- Comparative analysis across different persona types
- Sentiment analysis of qualitative feedback
- Prioritized issue identification and recommendations
5. Iterate and Improve
Continuous improvement cycle:
- Apply insights to refine your design
- Test iterations with the same personas for comparative analysis
- Track improvement metrics across versions
- Export reports for stakeholder presentations
Technology Stack
Frontend Technologies
Backend Technologies
AI & ML Technologies
Data & Analytics
System Architecture
Frontend Layer
API Layer
Core Layer
LLM Services
Vector DB
Image Services
Technologies & Solutions
Dynamic Persona Generation
Problem
Traditional personas are static, limited, and time-consuming to create, often lacking the diversity needed for comprehensive testing.
Solution
AI-powered persona generation using Pydantic models and LLMs to create realistic, diverse, and dynamically enhanced user personas.
Technologies
Benefits
- Generate personas in seconds instead of days
- Automatically infer realistic characteristics and relationships
- Customize personas for specific testing needs
- Ensure diversity and representativeness
Automated UI Analysis
Problem
Manual UI testing is subjective, inconsistent, and often misses critical usability issues across different user perspectives.
Solution
Modified OmniParser integration that automatically extracts UI elements, understands their function, and generates contextual questions.
Technologies
Benefits
- Automatically identify UI elements and their functions
- Extract text content for contextual understanding
- Map component relationships for user flows
- Generate targeted questions about specific UI elements
Structured Q&A System
Problem
Traditional feedback lacks structure, making it difficult to analyze and compare responses across different user types and designs.
Solution
A structured question-answering system that generates targeted questions based on UX dimensions and processes responses using Likert scales.
Technologies
Benefits
- Structured data collection for quantitative analysis
- Consistent evaluation across multiple designs
- Standardized metrics for tracking improvements
- Customizable question templates for different UX dimensions
Embedding-Based Similarity
Problem
Ensuring diverse and realistic persona traits that relate to each other in meaningful ways is challenging and time-consuming.
Solution
Vector embeddings stored in Qdrant enable semantic similarity searches and relationships between characteristics, enhancing persona realism.
Technologies
Benefits
- Find semantically similar characteristics for personas
- Deduplicate similar personas to ensure diversity
- Create realistic relationships between characteristics
- Build a growing database of persona traits over time
Comprehensive Result Analysis
Problem
Making sense of diverse user feedback and identifying actionable insights is often challenging and subjective.
Solution
Advanced analytics tools for analyzing QA results, including descriptive statistics, distribution plots, and visualization of problem areas.
Technologies
Benefits
- Identify patterns across different personas and questions
- Visualize problem areas in the UI with heatmaps
- Compare responses across different design iterations
- Generate actionable recommendations for improvements
Interactive Streamlit Interface
Problem
Complex UX testing tools often require technical expertise, limiting accessibility for designers and product managers.
Solution
Intuitive, responsive web application that simplifies persona creation, design testing, and result analysis without technical knowledge.
Technologies
Benefits
- User-friendly interface for non-technical team members
- Interactive visualizations for exploring results
- Seamless workflow from persona creation to testing
- Shareable results and export capabilities
Future Roadmap
Near Term
- Interactive heatmap overlays directly on designs
- Audio narration of persona feedback
- Enhanced PDF report generation
- Team collaboration features
Mid Term
- Automatic code suggestions for UI improvements
- Design version comparison tools
- Figma and Sketch plugin integration
- Video prototype testing support
Long Term
- Predictive UX performance metrics
- 3D and VR/AR interface testing
- Accessibility compliance automation
- Industry-specific persona libraries
Ready to transform your UX testing process?
Start gathering valuable insights from diverse AI personas in minutes, not days.