Acobot is an artificial intelligence tool. It works to engage customers, answer questions, and produce sales. Acobot generates leads from your website by asking visitors for their email address or telephone number straightforwardly. More importantly, it helps you achieve conversion rate optimization by nudging visitors to act as you expect with interactive call to actions at the right points. Acobot is fully automated. It does all the job and continuously optimizes the conversion rate by itself. The longer it works for you, the more results it delivers to you.
IBM Watson™ Assistant is highly flexible, allowing you to deploy small, focused solutions or to scale to enterprise wide deployments. With simplified tooling, it allows collaboration between business SMEs and developers to build out conversational solutions and advanced dialog flows, without needing to be an expert in machine learning. The premium and dedicated plans provide enterprise grade security and support; such as data isolation, end to end encryption and support for non-regulated PII data.
It also has a number of templates, covering bots built for shopify, woocommerce, livechat, restaurants and other templates which helped me understand how the different blocks come together to build a complex chabot. Voice conversation integration with alexa echo/google home is also coming up, along with web widgets if the existing twilio, telegram, facebook integrations are not enough already.
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.
Created in 1966 as an early natural language processing (NLP) computer program that emulates a Rogerian psychotherapist, a clinical practice that allows clients to take more action and progression in discussions. This is also known as person-centered therapy. Developed by Joseph Weizenbaum, ELIZA, named after a character in the play Pygmalion by George Bernard Shaw, is generally known as the first chatbot.
Chatbots, which are often called virtual agents or virtual assistants, are used in place of a human to conduct specific tasks or provide information based on written or spoken requests. This functionality includes both external, customer-facing requests and internal, employee-facing requests. Chatbots allow users to interact with an application in a conversational manner, whether textually or audibly, to perform certain functions.

msg.ai is an enterprise AI platform for customer service enabling companies to automate high-quality support on email, chat and social. msg.ai works alongside a company's human agents to respond to repeatable issues, offering convenient, immediate resolutions on the channels that matter most. The platform’s deep learning natural language understanding engine enables the AI to take the next best action, ensuring high-quality support every time. msg.ai easily integrates into an organization’s business systems, enabling companies to become proactive with support, alerting customers of an issue before they contact a company.
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.

It also has a number of templates, covering bots built for shopify, woocommerce, livechat, restaurants and other templates which helped me understand how the different blocks come together to build a complex chabot. Voice conversation integration with alexa echo/google home is also coming up, along with web widgets if the existing twilio, telegram, facebook integrations are not enough already.

Pros: It's system is more advanced comparing with Manychat or Chatfuel (both are like toys if you try Activechat). It has autorresponders of course, but also suitable for flexible AI conversations. Is like coding an advanced chatbot without needing to be a coder. The team is very responsive and their founder Andrii has a clear vision about this project.
Rulai also integrates with most messaging channels, customer service software, enterprise business software, and cloud storage platforms. You can either build a Ruali chatbot from scratch with its drag-and-drop design console and let its AI adapt to your customers or you can implement a pre-trained chatbot that has been fed data from your specific industry.

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