# Notes on Sinch's Global Chatbot Implementation Lessons ## Key Lessons Overview ### 1. Out-of-Scope Management - Treat as AI project, not IT project - Implement "99-intents" for out-of-scope handling - Address false positives and true negatives - Create effective fallback mechanisms - Plan for infinite user inputs ### 2. Intent Hierarchy - Organize from broad to specific - Enable direct access to specific information - Avoid redundant questions - Match user specificity level - Structure knowledge systematically ### 3. Expression Variation - Target 90-95% recognition rate - Account for regional/cultural variations - Balance comprehensiveness vs precision - Continuous model optimization - Regular expression updates ### 4. Error Response Strategy - Eliminate unhelpful responses - Provide alternative solutions - Implement safety net flows - Guide users to resolution - Maintain positive experience ## Implementation Framework ### Initial Development - Start with 70% recognition rate - Regular review of incoming questions - Iterative model updates - Continuous testing - Performance monitoring ### Optimization Process - Review unrecognized queries - Update training data - Test recognition improvements - Monitor false positives - Track success metrics ### Best Practices ### Project Management - Treat differently from traditional IT - Plan for continuous improvement - Regular model updates - User feedback integration - Performance tracking ### Technical Considerations - NLP model training - Intent organization - Expression variations - Error handling - Fallback mechanisms ## Common Pitfalls ### To Avoid - Traditional IT project approach - Limited intent scope - Poor error handling - Inadequate testing - Insufficient fallbacks ### To Implement - Comprehensive scope planning - Hierarchical intent structure - Robust error handling - Regular optimization - User-focused solutions ## Success Metrics ### Target Goals - 90-95% recognition rate - Effective error handling - User satisfaction - Problem resolution - Reduced frustration ### Monitoring Areas - Recognition accuracy - Error response effectiveness - User satisfaction - Resolution rates - System performance