Chatbot Development Using Dialogflow

Chatbots, Python Development, Machine Learning, Natural Language Processing (NLP)

As chatbots are gaining popularity day by day, the demand of chatbots development platforms is also rising. When you decide to delve into this exciting field of chatbots development, you will come across many platforms to assist you create your first chatbot application. The options are many and Dialgflow is one of them.

What is Dialogflow?

Dialogflow(Previously known as API.AI) is Google-owned AI powered chatbot development framework which comes very handy if you are looking to build a voice or text based bot. It’s a Machine Learning based natural language processor. Using Dialogflow you can provide delightful and natural conversational experiences to your customers.

If you are starting as a chatbot developer, then you must know the functionality provided by Dialogflow. So, let’s explore the basic features of Dialogflow.

Intents

Intents are basic building blocks of conversation in Dialogflow. Based upon voice/text input of users, Dialogflow selects best matching intent and replies back with response. And how does the matching process work? Using Training Phrases. In intent, you can define training phrases which will be matched with user inputs. As Dialogflow finds a matching training phrase, it will call upon corresponding intent and replies back to user with the response set in that intent.

Entities

Entities are Dialogflow’s mechanism for identifying and extracting useful data from natural language inputs. While intents allow your agent to understand the motivation behind a particular user input, entities are used to pick out specific pieces of information that your users mention. For example, in our Railway Buddy app, we defined Station Names as entities. So, whenever there was a station name included in the user input, we could identify it and user it to prepare response. Dialogflow offers some pre-built system entities too.

Knowledge base

This is currently in Beta version but it looks pretty promising. Knowledge base is kind of self learning system which takes FAQs or articles as input and prepares answers on its own. Isn’t it cool? You can give FAQ URL or upload an article in knowledge base and when user asks something, Dialogflow will find the matching response from FAQ/article and provide back to user. This will be game changing once the feature is matured.

Fulfillment

While intents are powerful way to prepare responses for the user, it might be able to handle all the responses. In cases, where responses are dynamic, you will need to fetch the data from your server. Fulfillment comes to your rescue for such scenarios. Dialogflow provides free of cost webhook integration to enable communication of your chatbot with your server. If you want to serve response from your database, then you can use webhook. Check our another blog post for detailed information about how to use webhook.

Integration

Wouldn’t it be great if you create a chatbot and use the same on multiple platforms? Well, Dialogflow just does that. It offers integration with wide range of chat platforms like Google Assistant, Facebook Messenger, Slack, Telegram, Line, Viber, Skype, Twitter, Twilio, Kik, Microsoft Cortana, Amazon Alexa and Cisco Spark.

It means that once you develop the chat agent, it can cater to your audience on different channels. Of course, there are some changes required to make the agent compatible with all these platforms, but the core conversation system stays intact. So, once your bot is developed on Dialogflow, with some modifications, it can be integrated on multiple platforms.

Analytics

Once your chatbot is live, you would be eager to know how your chatbot is performing. Analytics provide all the insights about usage of your bot. It helps you find more about user behavior so that you can improve your chatbot further.

Benefits of Dialogflow

  • Google Speech – one of the best Natural Language Processing(NLP) systems offered by Google.
  • Robust context based input recognition.
  • One bot can be integrated on multiple chat/messenger platforms.
  • Not only chat/messenger platforms, it also supports wearables and devices like Google Home and Amazon Alexa.
  • Free for normal use. The pricing depends upon the usage of the app as the usage increases. (more details below)
  • Multiple languages are supported. Currently supported languages are English, Danish, Dutch, French, German, Hindi, Indonesian, Italian, Japanese, Korean, Norwegian, Portuguese (Brazil), Russian, Spanish, Swedish, Thai.
  • Webhook integration to communicate with your server. This is very important as you might not be able to setup all the responses from Dialogflow itself. In case you need to fetch data or prepare response from your server then you can easily do it using Webhook fulfilment.
  • Analytics – when it comes to provide statistics Google never disappoints you. You can have detailed analytics report of your app.
  • Detailed error reporting. All the calls to your bots are logged so you can know how your users are using your app and what types of errors they are facing.
  • Easy import and export of chat agent.
  • You can count on Google infrastructure when you want to scale your apps to server millions of users.

Pricing

That platform offers 2 variants: Standard Edition and Enterprise Edition.

Standard Edition which is ideal for small to medium businesses or those who want to experiment with Dialogflow is free to use with some usage limitations. Unlimited Text based request, limited audio request capped monthly.
Enterprise Edition which is ideal for businesses that need to easily scale to support changes in demand from their users offers pay per usage type of pricing.

Community support and email support is available in Standard Edition while Enterprise customers are eligible for Cloud Support package with committed response time.

Overall Impression

Compared to other chatbots development platforms, Dialogflow has many advantages. Of course there are some limitations too, but it could be easily be number one choice for many types of chatbots development.

We have developed Railway Buddy app using Dialogflow which is currently live now on Google Assistant, Telegram and Facebook Messenger. We are pretty happy with the functionality Dialogflow has provided and recommend it to our customers.


Feel free to contact us or email at letstalk@pragnakalp.com for your chatbot development requirement. We would love to cater to your development needs at competitive rates with utmost quality and highest customer satisfaction.

3 Responses

  1. […] There are many platforms available to build bots for Messenger some of them are Manychat, Chatfuel, Dialogflow, Botsify etc. All of them are very good platforms with pros and cons each of their […]

  2. […] Dialogflow is a chatbot building framework that helps you build and deploy your own chatbots to multiple platforms like Google Assistant, Facebook Messenger, Telegram, Twitter, Slack, Line, Viber and many others. It is powered by a Machine Learning based NLU (Natural Language Understanding). The feature rich Dialogflow lets you create chatbot with ease. […]

  3. […] Chatbot Development Platforms like Dialogflow, IBM Watson, Amazon Lex, Microsoft Bot Framework, Chatfuel, Manychat, wit.ai, Botsify, Flow XO, […]

Leave a Reply

Your email address will not be published. Required fields are marked *