Dialogflow (formerly Api.ai) is a chatbot building tool, designed to give users new ways to interact with digital products by building engaging voice and text-based conversational interfaces powered by AI.
Dialogflow was acquired by Google in 2019.
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Rasa
Score 6.0 out of 10
Enterprise companies (1,001+ employees)
Rasa is a conversational AI platform from the company of the same name headquartered in San Francisco, enabling enterprises to build customer experiences. Rasa’s platform was built to create enterprise-grade virtual assistants, allowing personalized conversations with customers - at scale. Rasa’s conversational AI platform allows companies to build better customer experiences by lowering costs through automation, improving customer satisfaction, and providing a scalable way to gather customer…
Indicated for those who have good knowledge of programming and coding in HTML and JSON, that is, it is not suitable for beginners or users without much technical knowledge. It is suitable for those who want to integrate with various platforms, such as Telegram, Webhat, Facebook Messenger, among others. I also recommend it to anyone who needs to create a chatbot in several languages (it is not automatic translation). Recommended to create new projects in CX environment and not in ES.
I have been using the platform for over 3 years and I have noticed a very good evolution, in an attempt to reinvent themselves. The support team is amazing, always available to work out with us in achieving the best results. About the technology, the algorithms available in the platform suits most of the cases. Being language agnostic is a very positive point for us, because some big tech platforms have little support for PT-PT language.
Rasa CALM flows and Rasa domain could be made fully independent of the Rasa training process and dynamically retrievable from e.g. a graph DB. This would make the chatbot more flexible.
Prompt templates, or at least paths could be referenced in Rasa config. Different policies in the Rasa config could then be configured without code change to use different prompt templates
LLM configuration should rather be part of the endpoints, than model configuration.
Rasa Studio could support all the functionality of Rasa Pro.
Users benefit from Dialogflow's best User Interface and seamless User Experience. It's very scalable, and there are a lot of customization options to make it even more so. Dialogflow makes it simple to deploy, manage, and maintain chatbots. Artificial Intelligence algorithms make chatbots interactive, making it easier for users and chatbots to communicate and understand each other. Overall, it's a good option for those with little programming experience who want to learn Natural Language Processing.
With the help of dedicated team - documentation and video resources it is relatively easier to build. We prioritized pro-code usage to begin with launch.
Dialogflow is a wonderful tool that is helping to design customized chatbots. I personally recommend if you wanna know how it's works give it a try with a free APIs call, you'll love this tool
Rasa support has been very responsive, trying to fix any reported issues ASAP. They've also listened to many requests for improvement. The Rasa features and changelog are well documented
There is always use cases for both. We still use the other plattforms but each has its own strengths and weaknesses. We, as a contact center implementation partner always use multiple solutions both for ourselves but also for our customers to meet their needs. In the cases we choose Google Cloud Dialogflow is when we need to be able to handle specific follow-up questions from the customer. And for more complicated issues we also use a combination of this and other 3rd party plattforms. We always meet the need of our customers and as specialist and consultants we give expert advice on how to use all these different solutions in the best way possible.
Glean - proprietary semantic search algorithms, no backend actions integration IBM Watsonx - complicated dialogue builder, poor separation of no-code and pro-code interfaces ELMOS (agent based) - all logic in code, no dialogue logic in no-code interface possible Rasa - transparent and simple sharing of objects between no-code and pro-code interfaces. Transparent LLM usage and restrictions. Simple backend integration via Rasa SDK
As a partner to multiple contact center plattforms we have always been able to offer Google Cloud Dialogflow along with them because it integrates well with all.
Many businesses want to implement smart ways to have call deflection. Bots that can handle full dialogues with the customer is very intriguing to them because it can fulfill customers requests without using up as many resources
