Google’s Dialogflow is one of the most powerful tools available for building chatbots & AI-driven conversational agents. Whether you're looking to enhance customer support, drive sales, or automate workflows, Dialogflow makes chatbot development accessible and efficient.
It is easy to use, can handles the complex conversation, available in many languages, easy integration with other tools, easy webhook integration (HTTP request events on specific action inside Dialogflow system)
What is Dialogflow?
Dialogflow is a Natural Language Understanding (NLU) platform that helps developers create conversational interfaces for applications, websites, and messaging platforms like WhatsApp, Facebook Messenger, and Slack. It is powered by Google Cloud’s machine learning capabilities, allowing it to understand user intent and generate intelligent responses.
Google DialogFlow - CX vs ES
Google Dialogflow recently introduced Dialogflow CX (Customer Experience) – a powerful tool for creating advanced virtual agents. The older version of Dialogflow has been renamed to Dialogflow ES (Essentials). Dialogflow is now a common term to describe both the Dialogflow ES and CX. In this article, we can see the enhancements and limitations of Dialogflow CX vs ES.
Dialogflow CX provides a new way of designing virtual agents, taking a state machine approach to agent design. This gives a clear and explicit control over a conversation, a better end-user experience, and a better development workflow.
Dialogflow CX | Dialogflow ES | |
|---|---|---|
Agent types | Advanced, suitable for large or complex agents | Standard, suitable for small to medium agents |
Number of agents per project | Supports up to 100 agents | Supports one agent per project |
Conversation paths | Controlled by flows, pages, and state handlers | Controlled by intents and contexts |
Features | Streaming partial response, private network access, and continuous tests | Basic features like intents, entities, and contexts |
Additional information | Dialogflow CX is more user friendly and controlled by journeys or the flow via the page | Dialogflow ES has a free tier plan with limited quota and support. |
Pricing table
The following terms are used to describe pricing and quotas:
Request
A request is defined as any API call to the Dialogflow service, whether direct with API usage or indirect with integration or console usage. Depending on the task and design of the agent, the number of requests needed for an end-user to accomplish a task with a Dialogflow agent can vary greatly.
Session
A session is a conversation between an end-user and a Dialogflow agent. A session remains active and its data is stored for 30 minutes after the last request is sent for the session. A session can be either a chat session or a voice session.
- Chat session: A chat session only uses text for both requests and responses.
- Voice session: A voice session uses audio for requests, responses, or both.
Consumer Projects and Resource Projects
If you use multiple projects, it is possible that the project associated with your request authentication (consumer project) is not the same project that is associated with the agent in the request (resource project). In this case, the consumer project is used to determine prices and quotas. For more information, see Using multiple projects for Dialogflow ES or Using multiple projects for Conversational Agents (Dialogflow CX).
The following tables provide a pricing comparison for editions by agent type. Unless a feature is indicated as included, pricing is cumulative for all features used by a request.
Conversational Agents (Dialogflow CX) has a simpler pricing model than Dialogflow ES. For example, sentiment analysis has no charge for Conversational Agents (Dialogflow CX), but sentiment analysis incurs additional charges for Dialogflow ES.
Google DialogFlow Pricing - CX vs ES
Feature | DialogFlow CX | DialogFlow ES |
|---|---|---|
Text (includes all Detect Intent and Streaming Detect Intent requests that do not contain audio) | $0.007 per request | $0.002 per request |
Audio input (also known as speech recognition, speech-to-text, STT) | $0.001 per second | $0.0065 per 15 seconds of audio |
Audio output (also known as speech synthesis, text-to-speech, TTS) | $0.001 per second | Standard voices: $4 per 1 million characters WaveNet voices: $16 per 1 million characters |
Mega agent | NA | <=2k intents: $0.002 per request § >2k intents: $0.006 per request § |
Design-time write requests For example, calls to build or update an agent. | no charge | $0 per request |
Design-time read requests For example, calls to list or get agent resources. | no charge | $0 per request |
Other session requests For example, setting or getting session entities or updating/querying context. | no charge | $0 per request |
Google Cloud Platform costs
If you use other Google Cloud resources in tandem with Dialogflow, such as Google App Engine instances, then you will also be billed for the use of those services. See the Google Cloud Pricing Calculator to determine other costs based on current rates.
To view your current billing status in the Cloud console, including usage and your current bill, see the Billing page. For more details about managing your account, see the Cloud Billing Documentation or Billing and Payments Support.
Conclusion
Creating a chatbot with Dialogflow is a straightforward process that involves defining intents, training responses, and integrating with external platforms. But Heltar also provides a no code drag-and-drop chatbot builder that can be used by literally anyone and everyone because of its intuitive UI. By leveraging Dialogflow’s AI capabilities, businesses can build chatbots that provide seamless, intelligent, and automated conversations for customer interactions.
Want to integrate a WhatsApp chatbot for your business? Heltar offers the best solutions to help you get started with WhatsApp Business API-powered automation. Contact us today!
