Why is Expertime relying on Dialogflow to design your chatbot?

After testing most of the natural language processing and chatbot configuration tools available in the market, Expertime recommends Dialogflow to design your chatbot.

Dialogflow, which was acquired by Google back in 2016, is a natural language processing tool that is known for its reliability and openness. Without a doubt one of the best NLP (natural language processing) solution, benefiting from the power and ease of access Google is known for.

Expertime lists down the reasons behind this technical choice and its inclination towards using Dialogflow when developing chatbots.

C’est quoi un chatbot ?


What is a chatbot?

We have now entered a “conversation era”, and chatbot perfectly illustrates it. Just on Facebook Messenger, over a hundred thousand working bots on the platform.

More or less based on artificial intelligence, a chatbot is a robot that can have a text or voice discussion with a user, and that is accessible via one or several digital channels (website, mobile application, messaging app,…).

The role of a chatbot is to understand the user and to reply accurately to the request. It completes or replaces the human. This way, human being can be focused on more added value tasks than those handled and automated by the bot.



What is Dialogflow?

Previously called, prior to being acquired by Google, Dialogflow is a chatbot natural language processing engine. The NLP tool has 2 dimensions:

  • The understanding of the language (NLP) to interpret the user’s request (content and emotion);
  • And the ability to respond smoothly like a human could.


Dialogflow offers a complete chatbot development and deployment suite. It supports text as well as voice conversation. Many firms, such as KLM, The Wall Street Journal or Domino’s Pizzas have their chatbot run on this NLP solution.



The Dialogflow interface

What the console offers

Dialogflow has several building blocks in order to answer every situation. It enables the bot to manage a discussion, from its opening to its ending as well as to interact with external tools.


To do so, we configure:

  • Intents, namely the generic tasks a user plans to achieve with the chatbot. Let’s imagine that the aim of the chatbot is to give the weather to its users. It has the “Weather” intention and can answer the question “What is the weather?”
  • Entities to clarify the intention by adding a place and a date for example: “What will the weather (intention) be on Monday (entity) in Beijing (entity)?”. We will then be able to bounce back by asking complementation questions and progress in the scenario;
  • A set of possible typical questions. We set a larger scope of ways in which questions can be asked about the intention. Dialogflow then takes care of mixing the data to forecast other potential word combinations;
  • We potentially integrate external applications to extend functionalities (Google map localization, integration of a personal calendar, API with business apps databases,…). An openness that enables us to think of a great amount of potential actions.



The multiples advantages coming from Dialogflow

The Power of Google

Google puts in a lot of focus to develop performing conversation tool that are coupled with artificial intelligence. The solution that was acquired by Google in 2016, was then renamed Dialogflow and is now developed and maintained by the famous Mountain View firm, which is always a token of quality.



With its very accessible interface, Google focuses on ease of use, even for the novice. The console eases up data input. By offering a simplified interface, Google allows its users to benefit from a small learning curve.


Multiplicity of contexts of use

Google defends the principle of a single interface and a universal deployment. Dialogflows allows you to set up interactions via text and voice input. Your chatbot is accessible on several devices (computer, tablet, smartphone).

By default, it offers a quick integration within multiple platforms (Slack, Skype, Twitter, Messenger, Teams…), through existing and reliable connectors.

With 14 languages available, it offers multilingual chatbot project opportunities.


Fluidity brought by Artificial Intelligence

The user should be able to have a natural conversation with the robot. Google fulfills this mission by integrating artificial intelligence into its engine. This helps improving your chatbot by gradually completing the information already input in the interface.


Here is what Dialogflow does with Machine Learning:

  • Logical language associations such as “Hello” with “Hi”;
  • Management of sentence variations;
  • History preservation, providing a continuous experience;
  • Recognition of feelings and emotions to generate appropriate responses;
  • Understanding of words despite spelling and syntax errors;
  • Display of the response in record time



Dialogflow configuration by Expertime

Like all IT tools, Dialogflow requires expertime to master it and take full advantage of its potential. Although it is completely free and available to anyone (with an account and on the Google Cloud), the intervention of a specialist is recommended, unless you want to spend time understanding and configuring it, and ultimately go backward because of a lack of experience in its initial design.


How does Expertime operate when it comes to your chatbot project:

  • Requirement collection and analysis of the business need and vision for the project;
  • Recommendations on the most appropriate technologies;
  • Bot design (storyboarding of the conversation);
  • Technical configuration of the chatbot on Dialogflow;
  • Integration into a Framework;
  • Support to get familiar with the chatbot


Expertime has used Dialogflow to develop several chatbots:



Want to create a smooth and efficient chatbot for your business while taking advantage of the power and simplicity of Dialoglow? Get in touch!

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