8 Chatbot Development Frameworks: Building a Better Bot for Your Business

8 Chatbot Development Frameworks: Building a Better Bot for Your Business

04 Feb. 20
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There has been an explosion in the use of chatbots across both business websites and messaging applications, mainly because businesses want to cater to their customers and customers have a lot of queries that need to be answered. Managing these queries is difficult and cannot be done on a 24/7 basis unless you have a rotating team. One way to cut down operation costs and still provide a personalized customer experience is with chatbots. So, when it comes to the numerous chatbot development frameworks, knowing which one is right for your business can be a bit of a conundrum. This is why we have compiled a list of the most popular chatbot development frameworks that can help you build intelligent, adaptable, and productive chatbots. Whichever platform you choose, you will get a chatbot that is cost-effective, scales as you grow, and provides a personalized customer experience.

Which Platforms Are The Best, moving into 2020?

  • Microsoft Bot Framework – Build & Connect Intelligent Chatbots: The Microsoft Bot Framework that is used around the world by developers looking to build secure, scalable, solutions that integrate with current information technology ecosystems. The idea behind it is to help enterprises extend or expand their brand without losing control over data ownership. It is a rich framework that allows developers to develop, publish, and manage their bots all in one place, as it comes with two major components. First, the platform offers channel connectors, allowing you to connect the chatbot to messaging channels, and second, it comes with SDKs for implementing business logic into your conversations. Pros include pre-built options, machine learning speech to text implementation, is multilingual, has technical computer support, and works in multiple computer languages. The one con is that you have to choose to develop your chatbot in C# or Node.Js. can integrate with popular messaging applications like Facebook, Messenger, Slack, Skype, Cortana, and even websites.
  • Wit.AI – An NLP That’s Free to Use: The Wit.ai chatbot development framework is free to use, even for commercial entities, is open-source, and leverages community-based input to better the platform. While it is under Facebook’s branding, it started out as a Y Combinator Startup, which is an American seed accelerator company that invests funding into small companies. Due to the bot being open-source, over 200,000 developers have used it, allowing new developers to create chatbots with human-level interaction and intelligence. A lot of time is saved this way as the basics of human conversations do not need to be taught. Pros include being open source, has an incredible natural language processing engine, offers SDKs for IOS, Python, Ruby, and Node.Js, and supports over 80 languages. Plus, due to it being owned by Facebook, it is easily deployable on Facebook Messenger. The con with it is that some developers find that missing parameters are hard to retrieve. Can be integrated into any application, any website, Facebook Messenger, into home automation systems, into wearable devices and Slack.
  • DialogFlow – For Conversational Bots. The DialogFlow chatbot development framework is designed specifically around conversations, allowing developers to create highly intelligent chatbots and voice applications that can grasp the nuances of language. Over time, these chatbots continue to improve because they are supported by Google’s Cloud Natural Language, making it very easy for developers to train the chatbot to understand the finer details of human conversations. Yes, this includes human emotions and their connecting sentiments. With DialogFlow being a subsidiary of Google, it is built on Google’s infrastructure, allowing you to scale to millions of users and build actions for more than 400 million Google Assistant devices. Pros include the framework supporting voice and text-based assistants, is easy to learn from a development standpoint, provides rich conversations, has SDKs for 14 platforms, supports 20+ languages, has an in-line editor, provides sentiment analysis, and can even be programmed to carry out jokes, event searches, and payment handling. It has IoT integration for home automation as well. The con is that programmers do not have access to control over dialogue processing. Can integrate with Google Assistant, Facebook Messenger, Cortana, Kik, Skype, Telegram, Viber, Alexa, Slack and more.
  • IBM Watson – Perfect for Internal Use: The IBM Watson chatbot development framework is industry-leading, well-known, and one of the best platforms to use if you want to develop a retail, banking, Slack or voice-enabled Android chatbot. The platform comes with pre-configured content for customer care, banking, eCommerce, and utility content, making it extremely flexible. It is built on a neural network that is comprised of one billion words from Wikipedia and it uses machine learning to respond naturally to human queries. Pros include a highly advanced machine learning engine, automated predictive analysis, a Watson GUI for non-technical users, development can be stored on a private cloud, it comes with visual recognition security, supports 10 languages and has a built-in translator, and comes with a tone analyzer for understanding negative and positive responses. The con is that it can be a bit confusing to use if you are looking to create a very simple, non-AI powered chatbot, due to the number of tools available on the platform. Can integrate with WordPress websites, Intercom, Slack, and Facebook Messenger.
  • WordPress – A Module Based Option: The BotPress chatbot development framework takes quite a different approach in that it doesn’t require developers to implement their own dialogue manager, channels, or natural language understanding process because it comes with them all. This platform was built by developers as an open-source option with a user-interface so that non-technical individuals can manage the chatbots after they are deployed. It works on a module system which makes it fully customizable, and comes with a conversational flow management system, an NLU, actionable analytics, an authoring UI, and is multichannel. It can integrate with platforms like Skype, Telegram, Twilio, BotFrameWork, WebChat, Facebook Messenger, and SMS.
  • Rasa Stack – A Python-based Platform: The Rasa Stack framework is for developers, companies, and businesses that require contextual-based chatbots that can answer, understand, and execute on contextual circumstances. This platform is used widely in large companies within the banking sector, the sports industry, with job recruitment, and healthcare providers. Rasa is open source, automated text and voice assistants, and is made up of two major components. The first is the Rasa NLU which is their natural language processing engine, and the second is the Rasa Core, which uses intents and entities to understand queries. The pros of Rasa Stack are that it can manage contextual dialogues, can recognize intent, provides full data control, and allows you to create custom models. It can be integrated with Rocket. Chat, Slack, Twilio, Facebook Messenger, and Telegram.
  • ChatterBot – Based on Adaptability: If you are looking for a chatbot that can be trained in any desired language, ChatterBot is a fantastic option. It is powered by Node.Js and works by creating a Python library. While this chatbot will start off with no knowledge of how to communicate and with every human query, the chatbot saves the text that was entered and the text that the statement was issued for. The more input there is, the more accurate each response becomes as the chatbot learns how to communicate. Essentially, the chatbot will always choose the closest matching response by searching for the closest matching statement within its library and then returns the most likely response back based on the statement. Or in short, learns to communicate based on a collection of conversations in combination with machine learning. This is a good option for developers that need a bot to adapt based on conversation and continuous learning.
  • Amazon Lex. The Amazon Lex chatbot development platform is a part of the Amazon Web Services and comes with sophisticated bot-building tools. Like a few other platforms, it comes with built-in natural language understanding, machine learning, and numerous SDKs for different platforms. It allows the developer to input automated speech recognition that can be converted into text, can integrate with other Amazon Web Services and is free to use. Unfortunately, it is only available in American English at this time.

While all of these chatbot development platforms have their use-cases, it is important to note that the first few that you try may not be the right fit, as you will need to use one that best suits the kind of business that you have. If you have any questions about any of the above chatbot development frameworks or believe that one of these frameworks would work well for your business, please feel free to open up a conversation with us. Here at Lets Nurture, we build intelligent, conversational chatbots that help serve your customers around the globe with a personalized and tailored experience. The end result is a chatbot that can uplift your day-to-day operations, leaving you with more room to attend to critical business matters, while still providing excellent customer care. If you’d like to get in touch with us about an idea or with questions, please contact us or chat us up at +1-902-620-9098 . We’d love to help with your next project!

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Lets Nurture
Posted by Lets Nurture

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