Google Cloud Dialogflow Reviews

1. Google Cloud Dialogflow CX is like a playground for creating chatbots. It's super easy with its drag-and-drop interface and ready-made templates, making coding skills optional.

2. Since this product is from google, integrating with other Google Cloud services has become much easier. It's got everything—high availability, scalability, and even a safety net with fault tolerance. You can go serverless too, which means less hassle with managing infrastructure.

3. Dialogflow CX supports over 20 languages, making it a go-to for developers building chatbots and voice assistants for a global audience.

4. The deployment time for MVP is very minimal using Google Cloud Dialogflow when compared with other tools, making it go to too for the beginners.

The only downside is that if you want to use the fancy features in Dialogflow CX, you gotta go for the paid plans. So, for personal use, it's a bit limited with the free version.

Google Cloud Dialogflow gives me amazing UI where i can use drag and drop functionality to build a chatbot without any coding knowledge. It takes very less time to build a basic chatbot using Google cloud Dialogflow as it comes with predefined templates for multiple use cases.

What I like best about Google Cloud Dialogflow is its powerful natural language processing (NLP) engine. Dialogflow can accurately understand and respond to a wide range of user queries, even if they are complex or ambiguous. This makes it possible to create chatbots and voice assistants that can handle real-world conversations in a natural and engaging way.

I dislike Dialogflow's expensive pricing, difficult documentation, and unreliable support.

Google Cloud Dialogflow is solving the problem of building and deploying chatbots and voice assistants. It benefits users by providing a powerful and versatile platform that can be used to create chatbots and voice assistants that are informative, engaging, and helpful.

Makes collection of data and response to queries automation.

Improvements required for much better interface.

Data collection automated bot creation.

It's very easy to integrate with other technologies

Intend classification can be more precise and intuitive, ease of implementation.

It's best for the creating artificial agent

Best and cheaper services provided by Google cloud and with best scalability and some services and fully managed with best UI.

There are some services needs some clarity like some configuration which is blocked by Google itself.

Google Cloud is solving infrastructure , platform and software level services by providing individual services with best managed infrastructure.

Dialogflow made it easy for non-coders to create question/response results for our Hello PineView app for a high school. This was for a Girls Who Code club, and broadened exposure to creating applications. It was also quite easy to create intents that the girls coded to answer more complex questions via a call to our APIs.

It wasn't an issue with dialogflow per se, but how the whole google assistant creation hung together felt like 3 radically different applications. Google IAM, dialogflow, and there was another one in there for projects - and each web interface was radically different

Enabled us to create a google assistant voice application. It was educational for students, but also an actual useful application for the school.

Design studio and intuitive. Deployment and integration. I can tell it is one of the greatest tool to design and deploy quick chat solutions and easy to integrate

Can't think of any however it is better than EX. Have few troubles in interpret the digits

Creating better voice self service workloads

I'm pretty much impressed and like the way it is designed to work and it does.

As of now, I don't have much complains about so far we had used. But definitely we see more on AI assistance within dialog flow.

To design conversational flow for contact center services flows.

It's quite easy to configure the basic conversation flows, and then tweak it along the way

Still a limited limited in terms of handling complicated conversations which may cover multiple different topics

call deflection

Dialogflow supports context management, allowing conversations to be tracked and maintained over multiple turns. Contexts provide a way to carry session-specific information from one interaction to another, enabling more natural and context-aware conversations.

While Dialogflow provides flexibility in creating conversational agents, there might be limitations in customizing certain aspects of the platform. Users may find it challenging to implement highly specialized or complex conversational behaviors that go beyond the capabilities offered by Dialogflow's predefined features and templates.

Dialogflow leverages machine learning techniques to improve its understanding of user queries over time. It allows developers to train the model using example conversations and provides tools to evaluate and optimize the performance of the conversational agents.