Tech giants such as Google, IBM, Microsoft, Amazon, and Facebook are investing in conversational AI to make developers easily build chatbots. These AI-powered chatbots can automate various routine tasks such as sending emails, troubleshooting, searching for information on search engines, etc. For more on chatbots don’t hesitate to read our in-depth guide on conversational bots.
In this research we are focusing on a competitive chatbot platform on market owned by Google, Dialogflow. Other platforms are also compared with Dialogflow to see the advantages and disadvantages of each one.
What is Google Dialogflow?
Dialogflow, formerly api.ai, is a chatbot development platform acquired by Google in 2016. Under Google ownership, its was renamed as Dialogflow.
Wikipedia description of Dialogflow is, “Google-owned developer of human-computer interaction technologies based on natural language conversations.”
Dialogflow is a platform that can be used in designing conversational ai interactions such as chatbot, voice assistant, and virtual assistants, which are integrated with different conversational platforms, especially Google Assistant.
The main platforms that are compatible with Dialogflow are listed below. It can be integrated to all of the basic conversation platforms, except Whatsapp. Using other platforms such as Twilio, Dialogflow can be integrated into WhatsApp, too.
- Google Assistant
- Facebook Messenger
- Amazon Alexa
How does Google Dialogflow work?
On a high level, Dialogflow system works as described below:
- The user sends an input to the application through a device. This input can be a text or a voice message. This message is sent to Dialogflow.
- The incoming message is categorized by Dialogflow and matched with the intents defined by the chatbot developer. Chatbot developer can use training phrases to train the system in intent identification.
- A request is sent to the webhook service for an advanced scan of what action to take for this entry. The responses of the bot can be written directly by the developer or can be selected by Dialogflow. The dialogue system can be externally fed and developed through webhook and external APIs.
- Webhooks are structures that are automatically triggered according to defined actions and return HTTP response.
- Difference between an Application Programming Interface (API) and a webhook: An API needs to be triggered. Webhook is triggered automatically when a certain action takes place.
- The most appropriate action is reported to Dialogflow again as a result of external API and scanning in the database.
- Arranges the Dialogflow answer in order to convey the appropriate answer correctly in the integrated platform.
- Formatting is done in order to give the correct action in the application or device.
- The end-user receives the message.
How does it compare to other chatbot platforms?
Different chatbot development platforms can be evaluated in terms of ease of use, integration options, language support, and fees. Considering all these factors, Dialogflow is one of the most prominent platforms.
We reviewed these platforms:
- Google Dialogflow
- Amazon Lex
- IBM Watson Assistant
- Facebook’s Wit.ai
- Microsoft Azure Bot Service
Winner in conversational/ NLP capabilities: Unclear
This is an important factor, but it is hard to evaluate it objectively and draw conclusions in a quantitative way.
Winner in ease of use for non-technical personnel: All except wit.ai
All platforms provide easy use for both tech and non-tech employees except wit.ai. Wit.ai is developer-centric and it will not be the best option for non-tech employees.
Integration Platforms: Dialogflow is integrated to numerous platforms
Dialogflow is an advantageous one in terms of integration with various platforms. However, other chatbot platforms are also integrated to many platforms. For example, IBM Watson provides an integration to WordPress.
Wit.ai doesn’t provide direct integrations, however libraries available for various programming languages like python, node js. Therefore, developers can rely on Wit.ai as they build their conversational AI applications.
Language support: wit.ai is the winner with 50+ language options.
Dialogflow supports 20+ languages. IBM Watson supports 10+ languages in its beta version. Amazon Lex supports only English. On the other hand, wit.ai supports 50+ national and regional languages.
Cost: Wit.ai is the winner with free use for all. Other platforms provide limited free and extended paid plans
- Wit.ai is free for both personal and commercial use.
- Dialogflow has a free option for small and medium businesses. The enterprise version costs $0.002/request
- Azure bot service is also free for up to 10k messages per month. The paid plan starts from 0.0005 per message.
- Amazon Lex is free for the first year of use. After first-year voice and text requests cost different. Voice: 0.004/request. Text: 0.00075/request
- IBM Watson has a free plan with 10k messages/month and the paid plans start from 0.0025/message.
For which users is Dialogflow the right chatbot platform?
A non-tech small and medium business can integrate chatbots on their website for free by using Dialogflow. Dialogflow is a platform that enables the development of chatbot without the need for installation, technical infrastructure, and coding knowledge. It is easy to integrate in many different platforms directly without extra coding. Hence both non-tech and tech people can easily develop chatbots for their purpose.
You can also check out our guide on chatbot companies which also includes chatbot developers and developers of smaller platforms to provide an overview of the chatbot ecosystem.
If you have questions about how chatbots and Dialogflow can help your business, feel free to ask us:
Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.
Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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