Secrets of Creating a Killing Conversational AI Chatbot
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    Secrets of Creating a Killing Conversational AI Chatbot

    New Best Friend: Conversational AI Chatbot 

    Gone are the days when people used simple chatbots. Indeed, today any reputable business wants an AI-driven conversational chatbot. But do you know what it means in practice? We will tell you about it in the article below. Thus, from its name, we can tell that the Conversational AI chatbot includes these three main features: 1. It is a chatbot. What does it mean? A chatbot is a smart computer application that was specially created to conduct conversations via auditory or textual methods with the customers. Chat bots development is a step-by-step process of creating an application that allows interaction with users. What does it mean in practice? You want to book a holiday and by looking for the best results at the site, you see a message: “Hello, Can I help You?” Yes, that’s a simple example of a chatbot. It conducts primary conversations with the customers instead of a special employee working for that travel agency. From the technical side, this bot has a list of questions to answer and simply takes the right one corresponding to the topic. The technical side
    • Use either chatbot frameworks or SDKs. For instance, if you use the Landbot framework for creating conversational experiences that live online, no additional programming is needed.
    • To create a chatbot, use languages designed for creating a web API. The most popular ones are Node.js or PHP. But Java or Python is also a good way to go.
     2. It is conversational What does it mean? The program must be context-aware. Simply speaking, it should somehow maintain the state of the conversation and be able to reply to the user request in the current context. What does it mean in practice? For instance:
    • User — what is the weather like in New York today?
    • Bot — it's warm and sunny now, around 15C.
    • User — how about tomorrow? (Here, the bot should keep in mind that they were talking regarding the entity “weather” ( not, for example, a traffic jam or a reservation booking availability, even if these entities were discussed somewhere previously).
    The technical side
    • Take advantage of the cognitive computing APIs. Yes, the Cognitive APIs can be a great help as they let your chatbot offer a more personalized experience to your customers and internal stakeholders. The most popular Cognitive APIs are Watson discovery API, Language translation API, Text analytics API, Tone analyzer API, and MS QnA maker API.
     3. It is AI and machine learning-driven. What does it mean? The bot is powered by artificial intelligence and machine learning. Thus, unlike typical machine-based architecture, where everything is based on the possible if-else conditions programming for any possible conversation state, the AI bot learns each time any action takes place based on the special training data.   What does it mean in practice? Let’s imagine that your support chatbot SweetHome can’t answer the double-edged question (because the SweetHome chatbot can’t fully understand the content)—the chatbot sends this question to a human being and he or she responds instead. Meanwhile, the chatbot learns that that is how it should have responded. Therefore, the more conversations take place involving diverse conditions, the smarter the chatbot becomes. Yes, that’s an incredible self-learning creature.   The technical side There are special tools, which help your AI chatbots become smarter. For instance, Api.ai uses the machine learning model, Reacast.ai and wit.ai allow using all intents available for similar tasks. BotKit will help you create an AI chatbot.  The other simple framework is called Bottr, it’s written in Node.js and comes with a ready-made testing app. Gupshup’s platform is also great for bot building, testing, and deploying. Earlier the guesses that AI would perform some simple actions to help clients with their complicated ideas and problems could be considered as an innovative illusion. There is no possibility to apply additional software and precise algorithms for solution-finding. By now the technology of chatbots plays a crucial role in service for clients. Brands and companies are going to experiment and clients are aware of modern technologies and their possibilities. The modern application cases of chatbots and voice assistants become limitless and people may predict essential development in 2020. Let’s observe 5 chatbot trends in 2020.

    Intelligent chatbots and their improvement

    • Artificial Intelligence becomes more improved and smart
    The past years have been impacted by the constant growth of data volume. In 2020 the main task for AI is the use of received info. This technology also has effective ways of data improvement and analysis. Complex systems can check the data and find the prototypes and learn the principal laws and methods to gain the aims. The main difficulty is that machines can understand the info they get. Knowledge graphs help the chatbots to have access to basic knowledge and use them to recognize the info effectively and fast. It also concerns communication with customers and other operations. To be on top of the competition, companies must provide their client chatbots, which can say something useful at the necessary moment. According to customer answers, many users are irritated that chatbots have a lack of human interconnection. That’s why businesses add some funny and friendly answers to implement something human in conversation with a chatbot. If engineers are making responses for chatbots, they can use different services to improve it. This is very important that responses are written according to standards. They can use this info for improvement of interconnection with users, applying a big volume of data gathered in the past.
    • Higher concentration on gaining goals
    The improvement of AI systems goes ahead very quickly. The last results demonstrate AI superiority in strategy games and competition with professionals. There is a tendency that artificial intelligence will have powerful systems able to connect and transfer the info for better customer service. The ability to understand the information and to learn helps chatbots to be dominant in their sphere. They can assist people in finding solutions to rising problems. Their processing ability impresses experts. Chatbots are becoming more human. The majority of companies are expected to apply chatbots soon, clients demand chatbots to give personalized and effective support. Technology providers try to advance the correctness of requests, the understanding of human communication, cultural peculiarities, intentions of customers. Chatbots provide their services for enterprises and businesses. Apart from working with clients and finding solutions to their queries, AI-powered chatbots are predicted to offer more operations for companies. The chatbots optimize internal processes no accounting for their size. There are many types of chatbots, having different goals to satisfy the needs of companies. They include bots of human resources, workplace, marketing, data search, and others. Most enterprises are going to implement chatbots to improve their working efficiency. It makes sense to do it shortly to gain success in a deal.

    Peculiarities of chatbots

    • Change in operations
    Innovative kinds of social interconnections and networks are available due to chatbots.  In 2020 chatbots will transfer multiple tasks that directly help people find the right direction in problem-solving. One can gain the goal only in collaboration with human artificial friends such as chatbots. If people who are previously working with brands, surely they become a part of the company relationship system, where their cases are recorded and classified. When one uses it with chatbots, the technologies may apply the data to get a better understanding of customer’s problems and commentaries. Instead of beginning from scratch any session, a client and a chatbot may proceed to make a conversation referring to the previous problem. Obviously, according to privacy laws, the chatbot doesn’t have access to private info. Now, chatbots use the info the people provide on their public pages to find solutions to their requirements and problems. In 2020 it is expected the creators of chatbots will add analytics and useful data in them. It makes chatbots recognize prototypes and react to them correctly. In 2020 the developed chat-bots are AI-powered and deals with ML. It means that the more they are applied, the more they learn and the better they receive. Chatbots are often used for brand communication, that’s why they become better and more effective. The conversational chatbots learn the info about the clients, ordinary answers, and customer satisfaction levels.
    • Automated payments
    The automation of payment operations is becoming a trend in 2020. Chatbots help customers to order and buy products. A high percentage of companies are going to automate payments via different live chatbots. Chatbots suggest the simple process of payments which better the customer comfort level, reduce the number of delayed orders and ease the work of the sales team.
    • Voice recognition
    It is expected in 2020 that a big number of users prefer dealing with chatbots instead of writing questions in chats. This approach of receiving info saves time and allows clients to perform multiple tasks while communicating with chatbots. There is also the possibility of technological peaks connecting with human speech and their recognition. Chatbots have a disadvantage – their disability correctly to understand human language. One can say that even people can misunderstand each other. Moreover, machine intelligence does the same. If the scientists and engineers, working on AI, ML and NLP make a huge step in their development, the service, support, and sales are better and more effective. In some companies, the chatbots are presented as automated call centers that are responsible for client flow and service support. Healthcare is one of the pioneer industries to adopt chatbot technology.  Normally, all people deal with healthcare issues on a regular basis.  Hence, there is the need for any healthcare service provider to keep its customer service outstanding to retain its customers.  Many medical institutions are now served by chatbots as customer service 24 hours a day.  To achieve this without excessive reliance on manpower, ServReality has developed SwiftAnswer. ServReality designed the SwiftAnswer to be a customer service assistant, with the ability to serve even the largest medical chain.  It is powered by natural language processing technology. Made for a mini healthcare institution, SwiftAnswer can be used to reduce reception workload, by providing patients with swift answers to their requests at any time given. The chatbot helps patients get fast and correct answers to their questions.  From requesting the nearest drug prescription institution to Wi-Fi password, SwiftAnswer sends the required information to the Gmail address of the guests.  

    Introducing SwiftAnswer Chatbot for Healthcare by ServReality

    SwiftAnswer was created by the ServReality team consisting of a full-stack developer, a QA specialist, a Machine Learning/Natural Language Processing (ML/NLP) specialist, as well as a project manager.  The timeframe for its completion was two months.  Technologies incorporated in its development include:
    • Python (Flask)
    • Gmail API
    • Api.ai/Watson IBM
    • NLTK
    • MySQL
    • Sklearn
    • Gensim (Word2Vec)
    • Beautiful Soup.
    The SwiftAnswer consists of three parts:
    1. The chatbot itself
    2. The knowledge store
    3. The administrative panel.  The administrative panel is for the effective management of the bot knowledge, information and documents storage, and monitoring its conversations.
    The key functionalities of SwiftAnswer include:
    • Receiving and processing requests from users
    • Giving relevant and quick response, based on the stored data present in the knowledge store
    • Looking for documents in the database, to find the right answers to questions by the user.
    We often specify Swift for chatbot language. The project development process began with writing the technical specification.  After this, prototypes were prepared for the admin panel.  It took about two weeks to put the necessary things in place, before commencing the actual development process. The project was implemented in two months, with the team described above.  Using Scrum-ban - an event-driven approach to development, the ServReality team of experts worked in short repetitions, with one reputation planned ahead.  The team also drafted progress reports at the end of each sprint, in a bid to be quicker and more flexible. After creation, the chatbot was then trained to expand its capacity further. Ordinarily, the chatbot is designed to process about a thousand letters in 24 hours.  If the chatbot understands the details of the request, it will reply instantly. And the person will get the reply in his or her email box with the proper name, alongside an attachment if requested. In the case where the chatbot does not recognize certain keywords or combinations of words in the patient's request, a notification will be forwarded to the human operator, saying "I do not understand this request". If this happens, the operator will send the reply himself or herself. However, all unanswerable requests are sent to the language knowledge base for chatbot training, hence expanding its knowledge base. By making use of DialogFlow (Api.ai) and IBM Watson, the chatbot was designed to recognize language conversions.  The ServReality team also developed a Python algorithm that searches specific words in the email text and looks through the database for the required document. Conclusively, SwiftAnswer chatbot does not only bring speed and improved quality to customer service, but it also shed the workload of the healthcare institution staff. ServReality at this moment tips the chatbot to even become more powerful with time, and soon no human operators will be needed.

    The Bottom Line

    Anyway, Artificial intelligence has filtered into everyday life and today, adding AI chatbots to your business is becoming a question of when rather than if. In the span of the next few years, chatbot technology will become even more mature. How do you think, will it ever overcome the human brain? Please share your thoughts below.
    P.S. Do you want to enrich your business with a Conversational AI chatbot? ServReality is there to create your ultimate AI chatbot!



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