Amazon Lex is a service for building conversational interfaces into any application using voice and text. Amazon Lex provides the advanced deep learning functionalities of automatic speech recognition (ASR) for converting speech to text, and natural language understanding (NLU) to recognize the intent of the text, to enable you to build applications with highly engaging user experiences and lifelike conversational interactions. With Amazon Lex, the same deep learning technologies that power Amazon Alexa are now available to any developer, enabling you to quickly and easily build sophisticated, natural language, conversational bots (“chatbots”). Speech recognition and natural language understanding are some of the most challenging problems to solve in computer science, requiring sophisticated deep learning algorithms to be trained on massive amounts of data and infrastructure. Amazon Lex democratizes these deep learning technologies by putting the power of Amazon Alexa within reach of all developers. Harnessing these technologies, Amazon Lex enables you to define entirely new categories of products made possible through conversational interfaces. As a fully managed service, Amazon Lex scales automatically, so you don’t need to worry about managing infrastructure. With Amazon Lex, you pay only for what you use. There are no upfront commitments or minimum fees.
But even though most chatbots can handle moderately sophisticated conversations, like welcome conversations and product discovery interactions, the if/then logic that powers their conversational capabilities can be limiting. For instance, if a customer asks a unique yet pressing question that you didn’t account for when designing your chatbot’s logic, there’s no way it can answer their question, which hangs your customer out to dry and ultimately leaves them dissatisfied with your customer service.
But even though most chatbots can handle moderately sophisticated conversations, like welcome conversations and product discovery interactions, the if/then logic that powers their conversational capabilities can be limiting. For instance, if a customer asks a unique yet pressing question that you didn’t account for when designing your chatbot’s logic, there’s no way it can answer their question, which hangs your customer out to dry and ultimately leaves them dissatisfied with your customer service.
Alfred AI aims to transform humans into super-humans by strengthening their abilities. It's able to process text and audio specialized in CX in three languages. Spanish, Portuguese and English in which slang and other natural ways of language can be used. By implementing an innovative Machine Learning it understands and answers in a very friendly manner. Alfred AI is not just a bot is also a virtual agent able to respond chats, mails, tweets. FB, Instagram, WhatsApp and a phone call. It integrates with CRMs (Oracle Rightnow, Salesforce, Avaya) and other virtual agents such as Alexa or Siri but not limited to. One of the main difference with competitors is the fact that it only charges whenever a correct answer confirmed by the user is given. If a user states that the answer was not useful or it never answers then it won be charged. Alfred AI is different, is a CX specialist with empathy as main characteristic together with a high level of understanding.
Chatterbot Platform or Chatbot Software are computer program which are designed to simulate an intelligent conversation with one or more human users via auditory or textual methods, for engaging in conversation. Chatterbot are text based conversation agent which can interact with human users through some medium, such as an instant message service. The primary aim of such simulation has been to fool the user into thinking that the program's output has been produced by a human. Programs doing this are referred to as Artificial Conversational Entities, talk bots, chatterboxes, chatter robot, chatterbot, chatbot, or chat bot. Some of the chatterbots use natural language processing systems, and some others scan for keywords within the input and respond with a reply with the most matching keywords, or similar wording pattern, from a textual database. Chatterbots are often integrated into dialog systems for various practical applications such as offline help, personalised service, or information acquisition.

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