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Conversational AI chatbots can remember conversations
with users and incorporate this context into their interactions.

Any software simulating human conversation, whether powered by traditional, rigid decision tree-style menu navigation or cutting-edge conversational AI, is a chatbot.

The time it takes to build an AI chatbot can vary based the technology stack
and development tools being used, the complexity of the chatbot, the desired features,
data availability and whether it needs to be integrated with other systems,
databases or platforms. Advanced AI tools then map that meaning to the specific “intent” the
user wants the chatbot to act upon and use conversational AI to
formulate an appropriate response. Enterprise-grade, self-learning generative AI
chatbots built with a conversational AI product are continually and automatically improving.

The latest evolution of AI chatbots, often referred to as “intelligent virtual assistants” or “virtual agents,” can not only
understand free-flowing conversation through use of sophisticated language models, but even automate relevant
tasks. Such chatbots often use deep learning and natural language processing,
but simpler chatbots have existed for decades.
By initiating conversations at the right moment, such as
when a visitor appears interested in a particular service or
product, chatbots can turn casual browsing into meaningful interactions.
Furthermore, chatbots can be deployed on landing pages to boost conversion rates
by guiding users through the buying process or answering any
questions they might have. These AI-powered chatbots can be integrated
into websites, apps, or messaging platforms to provide reliable customer support.
Generative models enable the chatbot to generate relevant responses
in real-time, rather than relying on pre-set scripts.

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