An Amazon Lex bot can be developed via Console or REST APIs. With Amazon Lex different types of bots can be created including call center bots (to request a balance on an account, or schedule an appointment), informational bots (to access the latest news updates or weather), application bots (to book tickets), enterprise productivity bots (to check sales data from Salesforce), bots for the healthcare industry, and for Internet of Things. AgentBot integrates with any CRM, internal system, human chat, or third-party application through the REST API.Īn easy to use Amazon Lex service allows you to build, test, and deploy conversational interfaces for different applications using voice and text with embedded deep learning technologies for speech recognition, speech to text conversion, and natural language understanding. AgentBot answers may contain formatted text, videos, related FAQs, buttons, web view extensions, carrousels, forms, pdf files, images, co-browsing, emoji, integrations or external forms, or maps complement. AgentBot learns constantly, from every interaction. AgentBot is also able to recognize voice, emoji, and stickers to detect keywords, to segment customers, to predict the next question. The NLU engine understands users’ intents even if it contains multiple ways of asking, local terms, regionalisms, jargon, grammatical errors, and other language deviations. The platform has enough memory to maintain coherence during long conversations, gathers customer information to deliver customized solutions, and continually evolves. AgentBot uses Aivo’s natural language understanding engine. The platform provides its own algorithms, dictionaries and meanings database (the largest base of different ways of expressing the same meaning). The tool doesn’t require any linguistic or technical skills and can work with any text or voice channel. There are even platforms (Imperson, in particular) that offer to create a chatbot that will speak using the right voice and a special unique personality for your brand.īelow is an overview of the most popular bot platforms.ĪgentBot, an automatic customer service solution, was developed in Latin America and supports English, Spanish, and Portuguese languages. Several startups were acquired by bigger companies: Api.ai was acquired by Google, Semantic Machines was acquired by Microsoft, Motion.ai was acquired by Hubspot, KITT.AI was acquired by Baidu, ChattyPeople was acquired by MobileMonkey. Many of them grow communities where it is possible to find answers on questions about the platforms. Some of the chatbot building tools are provided with step-by-step instructions of the bot building process in text or video format. The most popular and functional NLP tools are IBM Watson, Amazon Lex, Microsoft LUIS, Google Dialogflow, Wit.ai, Rasa, DeepPavlov.ai, Electra.AI, DigitalGenius, and Semantic Machines. Usually, such platforms don’t include their own NLP engines, but integrate third-party NLP tools (conversational AI). The analytics shows metrics of the chatbot’s and agent’s performance like total users, user engagement and activity, number of conversations, average conversation length, hot topics and keywords, most frequently used intents and exit percentages, answered and unanswered questions by the bot, and so on. The newest startups that appeared in 2017–2018 are mostly platforms with code-free visual conversation builders that provide beautiful dashboards with analytics. During last few year many local chatbot building tools were developed: Recast.AI in France, Xenioo in Italy, Rasa in Germany, DeepPavlov.ai and Electra.AI in Russia, AgentBot in Argentina, Botsify in Pakistan, Engati and Morph.ai in India, and others. Others are frameworks containing advanced tools for developers like APIs, SDKs, IDEs, and others. Some of them are platforms that do not require any programming skills and include visual flow builders. All the fifty tools are different and have their unique features.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |