Learn the difference between Google’s Dialogflow versus Azure Bot Service. If you are planning on creating a chatbot with two large cloud providers, this post will talk about the differences between these two services.
If your team is thinking about creating a chatbot, researching the two largest cloud providers out there would be a great starting point before venturing into contracting with more boutique services.
One of the things I learned during my projects was use the technology that is accessible (meaning, not requiring a lot of business political gates through the PMO for investment). Cloud service providers make it easy to spin up and provision servers and services and decreases the time to market.
With a chatbot, the best thing you could do is spend time with a single skill and then launch it with some expectations set. The data that you get from launching a chatbot will be one step towards a project where you can mine data and understand truly what users are expecting.
Two large providers, Google Cloud Platform and Microsoft Azure, have services already available so that you can create your own chatbot quickly.
My intent with this post is to share with you a comparison between these two providers specifically. We’ll go into detail on comparing the features.
Main Difference Between Dialogflow and Bot Service
Bot Service works with Bot Framework as a platform to build chatbots using open source SDKs, tools, and services (like the Bot Emulator) which will enable you to develop quickly and easily. There is also a Visual Interface for non-developers to utilize as well.
Dialogflow was known initially as API.AI before it was acquired by Google. It provides a web interface that allows both non-developers and developers to create bots. It is a closed source service with APIs and a web interface. Users can interact with the bot using voice and text-based conversational interfaces.
About Dialogflow from Google
In 2016, Google acquired Dialogflow and then added it as a service on the Google Cloud Platform. The web and user interface console makes it really easy to create a basic chatbot that can then be added to any web application, allowing users to quickly understand the differences between intents and entities without having previous knowledge. There is a web demo option to integration into a website, but it is very rudimentary. Developers will need to create their own UI and integrate it with the APIs from Dialogflow. The UI can easily be transformed with simple CSS and HTML.
About Bot Service from Azure
In 2016, Microsoft launched Azure Bot Service to enable chatbot creators to move to the cloud and allow Microsoft to manage server and storage considerations. Microsoft has a desire to create a robust and large bot directory and chatbot search engine using this platform, so bots that utilize Azure Bot Service will be added to the Microsoft Bot Directory automatically .The service provides templates and SDKs using the Bot Framework and works well with other Azure services like QNAMaker and LUIS.
Integration Comparison Between Dialogflow and Bot Service
Google Dialogflow integrations include Google Assistant, Slack, Facebook Messenger, Twitter, and Twilio. This provides a full list of the channels Dialogflow is able to support.
Bot Service integrations include Cortana, Facebook Messenger, Skype, Kik, Telegram, and Twilio. This provides the full list of channels bot service is able to support.
Web and Mobile Integrations – Dialogflow vs Bot Service
Google Dialogflow has codeless, basic built-in web integration (check out the WordPress tutorial for integrating a chatbot with Dialogflow).
Azure Bot Service supports open source web chat widgets that are all available in Github.
Google Dialogflow vs Azure Bot Service Languages
Google Dialogflow supports over 20 languages which include English, Spanish, Portuguese, French, Hindi, and Chinese.
Azure Bot Service over 15 languages including English, Spanish, Portuguese, French, Hindi, Arabic, and Chinese.
Cost Difference Between Google Dialogflow vs Azure Bot Service
Google Dialog flow has a free standard plan that can be used by small to medium sized businesses. Google Dialogflow Enterprise edition costs $0.0002 per request.
Azure Bot Service is free up to 10,000 messages per month. The paid plans start from $0.50 per 1,000 messages with additional charges for consuming other services like Azure Functions and Azure Web Apps.
Whether you are using Dialogflow or Bot Service building your first chatbot, ensuring that you know what the use cases are will be important to ensuring the foundational architecture will support the current and future use cases for the bot. Understanding the value proposition for a chatbot will help you understand where your team or organization is headed in terms of future functionality. Chatbot services are still maturing, and I do believe that we are in the early stages as adoption continue to arise and tooling becomes more sophisticated.
If you are starting out and unsure with what your chatbot will do, I would recommend going to one of the larger cloud providers and utilizing their chatbot service first to create a prototype, and then move/scale as you increase adoption of the chatbot.
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