Comparing The Top Bot Development Frameworks

Now that we have differentiated between bot development frameworks and platforms, let’s deep dive into some of the most popular bot frameworks and their different features and capabilities.

Microsoft Bot Framework is one of the most comprehensive frameworks for building enterprise chatbots. You can build a simple Q&A bot or a sophisticated virtual assistant.

It is not only intelligent and feature-rich, but it’s also flexible and scalable. Developers can build bots that interact with users in a natural language. This is enabled by Microsoft’s Language Understanding Intelligent Service (LUIS) which extracts intents and entities from conversations. With LUIS, you can constantly improve the natural language models.

The Bot Connector feature of this framework allows bot integration of a variety of platforms such as Slack, Facebook Messenger, Telegram, Webchat, SMS, email, Skype etc.

It also leverages Microsoft’s QnA Maker which allows you to build basic QnA bots based on existing FAQ URLs, structured documents and product manuals.

One of the main advantages of the framework is that it supports Azure Bot Service. Azure allows you to quickly respond to user queries, even if there is high volume. And by using Azure Bot Service, you only have to pay for messages delivered using the Premium channel. In addition, with the service you can have complete ownership and control over data.

Another benefit of this framework is that it provides an open source SDK to build and test chatbots. You can also test and debug bots with Microsoft’s desktop application – Bot Framework Emulator.

Learn More: Why CIOs should consider Microsoft Bot Framework to build Enterprise Bots

WIT.AI

Facebook’s Wit.ai is a natural language bot development framework which enables developers to build both voice and text based bots on virtually any messaging platform of their choice.

It also allows developers to build voice interface for their apps. Moreover, the platform also shares the bot learnings with the developer community who can leverage it to further enhance the user experience.

Additionally, Wit.ai is an effective solution for home automation. It can control any smart device including home appliances and wearables.

Pre-build entities like temperature, URLs, emails, etc. make Wit.ai an excellent virtual assistant. However, the developers may have to work on refining engine training which currently takes a little long.

Dialogflow

Dialogflow, previously known as API.AI, runs on the Google Cloud platform. Powered by Google’s machine learning, it enables bot to understand the intent of the user and respond in the most accurate manner. It also takes user-machine interaction to a new level with voice and text-based conversational interfaces.

It can be integrated with any platform including Google Assistant, Alexa, Cortana, Facebook Messenger, Slack, websites and many more. Dialogflow also supports almost all types of devices such as wearables, phones, car audio, smart devices etc. This means you can connect with your users irrespective of which devices or platforms they’re using. With its ability to support over 20 languages, it helps you expand your global reach.

Another benefit that this framework offers is that it allows fast coding, thus allowing quicker time-to-market.

RASA Stack

Rasa is another open-source framework which is powered by machine learning. It can be customized fully which makes it a fit choice in enterprise architecture. There are two main components of this framework – Rasa NLU and Rasa Core. Rasa NLU is a natural language processing tool which classifies intents and extracts entities in chatbots. It analyses free text and takes out structured data from it. For example – address, date, numbers etc. Rasa Core uses intents and entities of Rasa NLU to create a reply dialogue. The deep learning technology empowers it to conduct complex conversations.

Rasa’s powerful and intuitive interface facilitates faster training and improves user experience.