Intents
Learn the fundamentals of Intents and how they’re used in Cognigy.AI to enhance conversational AI capabilities
NLU Performance Tuning
Fine-tune Intent recognition by analyzing accuracy and confidence. Adjust thresholds to optimize detection sensitivity
Rules and Conditions
Define rules and conditions to refine Intent handling, ensuring accurate user input recognition and response
Slots
Use Slots to extract data from user input, enabling dynamic interactions within conversations
Affirmative Words
Configure words and phrases for affirmative recognition, improving AI Agents understanding capabilities
Intent Hierarchy
Structure and prioritize Intents to improve recognition and mapping accuracy
Attachments
Attach additional resources like Flows and Lexicons to enhance Intent processing and response generation
External NLU
Integrate third-party NLU services for extended Intent recognition and language processing capabilities
Miscellaneous
Explore additional NLU tools