Design intents, add training phrases, write responses — then chat with the bot you built! See exactly how real chatbots like Siri and Alexa work inside.
An intent is the "goal" behind a message. "What's the weather?" and "Will it rain?" are the same intent: asking about weather.
Many ways of saying the same thing. The more phrases you add, the smarter your bot becomes at recognising user messages.
The bot compares your message to all training phrases using keyword similarity and picks the best matching intent.
A grid showing which intents the bot gets right vs. confuses. The diagonal should be bright green for a good bot!
You designed intents, trained your bot, and analysed its confusion matrix!
The meaning behind a user message. "Book a flight" and "I want to fly to Delhi" are the same intent.
The set of example phrases that teach the bot what each intent looks like. More = better.
A number between 0–1 showing how confident the bot is about its chosen intent. Below 0.3 = confused.
A table showing correct vs. incorrect predictions. Engineers use this to find which intents need more training data.
When confidence is too low, the bot uses a fallback response: "Sorry, I didn't understand that."
Natural Language Processing — the field of AI that helps computers understand human language.