Product: SaralPolicy
Version: 1.0
Author: Vikas Sahani (Product Manager)
Engineering Team: Kiro (AI Co-Engineering Assistant), Antigravity (AI Co-Assistant)
Date: January 2026
Demographics:
- Age: 28, Software Engineer
- Location: Bangalore
- Income: ₹8L per annum
- Tech-savvy, English and Hindi speaker
Goals:
- Understand health insurance policy before purchase
- Compare different insurance options
- Avoid claim rejections due to misunderstanding
Pain Points:
- Complex policy language
- Hidden exclusions and conditions
- Fear of claim rejection
- Lack of insurance knowledge
Behavior Patterns:
- Researches online before making decisions
- Prefers digital solutions
- Values transparency and clarity
- Willing to pay for quality service
Demographics:
- Age: 35, Business Owner
- Location: Mumbai
- Income: ₹15L per annum
- Manages multiple insurance policies
Goals:
- Understand business insurance policies
- Ensure adequate coverage for business
- Manage multiple policies efficiently
- Avoid coverage gaps
Pain Points:
- Multiple complex policies
- Time constraints for policy review
- Business-specific coverage needs
- Risk management complexity
Behavior Patterns:
- Delegates tasks when possible
- Values efficiency and time-saving
- Prefers comprehensive solutions
- Willing to invest in business protection
Demographics:
- Age: 62, Retired Government Employee
- Location: Delhi
- Income: ₹5L per annum (pension)
- Limited tech knowledge, Hindi speaker
Goals:
- Understand existing life insurance policy
- Ensure family is protected
- Navigate claim process
- Get help with policy questions
Pain Points:
- Complex policy language
- Limited digital literacy
- Fear of being cheated
- Need for human assistance
Behavior Patterns:
- Prefers human interaction
- Values trust and reliability
- Needs simple explanations
- Relies on family for tech help
Touchpoints:
- Google search for "insurance policy analysis"
- Social media advertisement
- Friend recommendation
- Insurance agent referral
Emotions: Curious, skeptical, hopeful Actions:
- Visits SaralPolicy website
- Reads about features and benefits
- Checks pricing and plans
- Reviews testimonials and ratings
Pain Points:
- Uncertainty about service quality
- Concern about data privacy
- Price sensitivity
- Time constraints
Touchpoints:
- Website registration
- Email verification
- Profile setup
- Tutorial and help
Emotions: Excited, cautious, learning Actions:
- Creates account with email
- Verifies email address
- Completes profile information
- Watches tutorial videos
Pain Points:
- Registration process complexity
- Email verification delays
- Information overload
- Technical difficulties
Touchpoints:
- Document upload
- AI processing
- Results review
- Q&A interaction
Emotions: Anxious, hopeful, surprised Actions:
- Uploads health insurance policy PDF
- Waits for AI analysis (30 seconds)
- Reviews bilingual summary
- Asks questions about coverage
Pain Points:
- Upload process complexity
- Waiting time anxiety
- Understanding results
- Trust in AI accuracy
Touchpoints:
- Results interpretation
- Comparison with other policies
- Expert consultation (if needed)
- Final decision
Emotions: Confident, relieved, satisfied Actions:
- Reviews detailed analysis
- Compares with other options
- Consults with family
- Makes informed decision
Pain Points:
- Information overload
- Decision paralysis
- External pressure
- Time constraints
Touchpoints:
- Policy purchase
- Ongoing support
- Claim assistance
- Renewal reminders
Emotions: Satisfied, protected, grateful Actions:
- Purchases recommended policy
- Saves analysis for reference
- Receives ongoing support
- Gets claim assistance
Pain Points:
- Ongoing support needs
- Claim process complexity
- Renewal reminders
- Policy changes
Touchpoints:
- Business growth
- New insurance requirements
- Policy review needs
- Risk assessment
Emotions: Concerned, overwhelmed, determined Actions:
- Identifies coverage gaps
- Reviews existing policies
- Seeks professional help
- Researches solutions
Pain Points:
- Complex business requirements
- Multiple policy management
- Time constraints
- Cost considerations
Touchpoints:
- Online research
- Professional consultation
- Solution comparison
- Vendor evaluation
Emotions: Analytical, cautious, hopeful Actions:
- Researches business insurance solutions
- Consults with insurance advisors
- Compares different options
- Evaluates SaralPolicy for business use
Pain Points:
- Information overload
- Conflicting advice
- Time constraints
- Budget limitations
Touchpoints:
- Account setup
- Policy upload
- Analysis and review
- Implementation planning
Emotions: Excited, cautious, optimistic Actions:
- Sets up business account
- Uploads multiple policies
- Reviews comprehensive analysis
- Plans implementation strategy
Pain Points:
- Setup complexity
- Multiple policy processing
- Analysis interpretation
- Implementation planning
Touchpoints:
- Regular policy reviews
- New policy analysis
- Claim assistance
- Risk monitoring
Emotions: Confident, satisfied, proactive Actions:
- Schedules regular reviews
- Analyzes new policies
- Gets claim assistance
- Monitors risk exposure
Pain Points:
- Ongoing management
- Policy changes
- Claim complexity
- Risk assessment
Touchpoints:
- Policy document review
- Family consultation
- Agent interaction
- Problem recognition
Emotions: Confused, worried, frustrated Actions:
- Reviews policy documents
- Consults with family
- Contacts insurance agent
- Identifies understanding gaps
Pain Points:
- Complex policy language
- Limited understanding
- Family dependency
- Agent communication issues
Touchpoints:
- Family assistance
- Online research
- Service discovery
- Solution evaluation
Emotions: Hopeful, skeptical, dependent Actions:
- Gets family help with technology
- Researches online solutions
- Discovers SaralPolicy
- Evaluates service suitability
Pain Points:
- Technology barriers
- Information overload
- Trust issues
- Family dependency
Touchpoints:
- Family-assisted setup
- Document upload
- Analysis review
- Understanding results
Emotions: Grateful, relieved, confident Actions:
- Gets family help with setup
- Uploads policy documents
- Reviews analysis with family
- Understands policy details
Pain Points:
- Technology dependence
- Analysis complexity
- Family involvement
- Ongoing support needs
Touchpoints:
- Regular consultations
- Policy updates
- Claim assistance
- Family support
Emotions: Supported, confident, satisfied Actions:
- Receives regular support
- Gets policy updates
- Accesses claim assistance
- Maintains family involvement
Pain Points:
- Ongoing technology needs
- Policy changes
- Claim complexity
- Family dependency
User Goal: Upload insurance policy for analysis User Actions:
- Navigate to upload page
- Select document file
- Confirm upload
- Wait for processing
Emotions: Anxious, hopeful, impatient Pain Points:
- File format confusion
- Upload size limitations
- Processing time uncertainty
- Technical difficulties
Opportunities:
- Clear upload instructions
- Progress indicators
- Format validation
- Error handling
User Goal: Receive accurate policy analysis User Actions:
- Wait for AI processing
- Review analysis results
- Understand key points
- Ask follow-up questions
Emotions: Curious, skeptical, relieved Pain Points:
- Processing time anxiety
- Result interpretation
- Trust in AI accuracy
- Question formulation
Opportunities:
- Real-time progress updates
- Clear result presentation
- Confidence indicators
- Guided Q&A
User Goal: Get expert validation for complex cases User Actions:
- Receive HITL notification
- Wait for expert review
- Review expert feedback
- Understand validation
Emotions: Concerned, grateful, confident Pain Points:
- Review time uncertainty
- Expert feedback complexity
- Validation understanding
- Trust in expert opinion
Opportunities:
- Clear HITL explanation
- Expert credentials display
- Feedback interpretation
- Validation confidence
User Goal: Ask questions about policy User Actions:
- Think of questions
- Formulate question
- Submit question
- Wait for answer
Emotions: Curious, uncertain, hopeful Pain Points:
- Question formulation
- Language barriers
- Question relevance
- Answer expectations
Opportunities:
- Question suggestions
- Multi-language support
- Question templates
- Answer previews
User Goal: Receive accurate, helpful answers User Actions:
- Read answer
- Understand content
- Check source citations
- Ask follow-up questions
Emotions: Satisfied, confused, curious Pain Points:
- Answer complexity
- Source understanding
- Follow-up questions
- Answer accuracy
Opportunities:
- Clear answer presentation
- Source explanations
- Follow-up suggestions
- Accuracy indicators
User Goal: Access policy analysis on mobile User Actions:
- Download app
- Login to account
- Access policy analysis
- Use mobile features
Emotions: Convenient, satisfied, engaged Pain Points:
- App download
- Login process
- Mobile interface
- Feature limitations
Opportunities:
- Easy app download
- Biometric login
- Mobile-optimized interface
- Full feature access
Impact: High (affects all users) Frequency: Very High User Segments: All Current State: Users struggle with legal language Desired State: Clear, simple explanations Solution: AI-powered plain language translation
Impact: High (affects adoption) Frequency: High User Segments: All Current State: Skepticism about AI accuracy Desired State: Confidence in AI results Solution: HITL validation and transparency
Impact: Medium (affects seniors) Frequency: Medium User Segments: Senior citizens Current State: Limited tech literacy Desired State: Easy-to-use interface Solution: Simplified UI and family support
Impact: Medium (affects satisfaction) Frequency: High User Segments: All Current State: 30-second processing time Desired State: Faster processing Solution: Performance optimization
Impact: Medium (affects decision-making) Frequency: Medium User Segments: All Current State: Too much information Desired State: Prioritized information Solution: Progressive disclosure
Impact: Medium (affects conversion) Frequency: Medium User Segments: Price-sensitive users Current State: Concern about service cost Desired State: Value for money Solution: Freemium model and value demonstration
Impact: Medium (affects usage) Frequency: Medium User Segments: Mobile users Current State: Limited mobile features Desired State: Full mobile experience Solution: Native mobile apps
- Progressive Disclosure: Reveal features gradually
- Interactive Tutorials: Hands-on learning
- Success Metrics: Track onboarding completion
- Personalization: Customize based on user type
- Transparency: Show AI confidence scores
- Expert Validation: Display HITL reviews
- Source Citations: Provide document references
- Testimonials: Share user success stories
- Multi-language Support: Hindi and English
- Simplified Interface: Easy-to-use design
- Family Support: Multi-user accounts
- Offline Capability: Basic features offline
- Faster Processing: Reduce analysis time
- Progress Indicators: Show processing status
- Caching: Store results for quick access
- Mobile Optimization: Responsive design
- Onboarding Completion Rate: 80%+
- Feature Adoption Rate: 60%+
- User Satisfaction Score: 90%+
- Net Promoter Score: 70+
- Retention Rate: 70%+ (3 months)
- Daily Active Users: 40% of registered users
- Session Duration: 5+ minutes average
- Feature Usage: 3+ features per session
- Return Visits: 60%+ monthly return rate
- Mobile Usage: 50%+ mobile traffic
- Conversion Rate: 10%+ (free to premium)
- Customer Lifetime Value: ₹2,500+
- Customer Acquisition Cost: ₹500-
- Churn Rate: <10% monthly
- Revenue per User: ₹200+ monthly
Next Steps: Implement user experience improvements based on journey analysis, focus on onboarding optimization and trust building initiatives.