Google’s Dialogflow – natural language understanding platform for conversational user interface & interactive voice response system

Dialogflow is a natural language understanding platform that makes it easy to design and integrate a conversational user interface into your mobile app, web application, device, bot, interactive voice response system, and so on. Using Dialogflow, you can provide new and engaging ways for users to interact with your product.

Dialogflow can analyze multiple types of input from your customers, including text or audio inputs (like from a phone or voice recording). It can also respond to your customers in a couple of ways, either through text or with synthetic speech.

Dialogflow CX – Dialogflow Customer Experience

Dialogflow CX is an advanced development suite for creating conversational AI applications, including chatbots, voicebots, and IVR bots.

It includes a visual bot-building platform, collaboration and versioning tools, advanced IVR feature support, and is optimized for enterprise scale and complexity. Dialogflow CX is cross platform and can connect to your own apps, existing telephony platforms, and digital platforms. Dialogflow CX users have access to Google Cloud Support and a service level agreement (SLA) for production deployments.

Dialogflow CX allows chatbots with higher complexity to be built more seamlessly using a visual editor and not require one to write complex code.

steps –

Flows and Pages as Building Blocks:

Flows and Pages are the building blocks of a CX agent. In the conversation path visualization graph, pages are the nodes. The pages manage the operations that the user performs within a flow.


Flows are like sub-agents. We can think of flows as Dialogflow ES Mega Agents. In CX, the mega agents are replaced by great flexibility in managing flows, which can also be developed by different teams. An agent can have any number of flows. Each flow is associated with multiple pages.


In the ES version, the context was used to determine the control of the conversation flow. Dialogflow CX completely eliminates the concept of the input and output contexts. Instead, pages are used to move the conversation forward.

The most interesting part is the interactive visualizations that allow developers to quickly see, understand, and edit their work. ES is mostly text-based editing. However, CX has a visual flow graphical editor to design our conversation paths.


Every page has the following elements:

Entry Dialog – defines the agent’s response when a page is active. At any point in the conversation, only one page is considered active and the flow associated with that page.

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Parameters – are used to collect critical information from the end-user. In Dialogflow CX parameters have a session-level scope. This means, when we collect user input, we need some way to keep track of what information they provided in the prior steps. In Dialogflow ES, we have a concept of context lifespan for this purpose. But in CX, session-level parameters are built-in automatically.

Routes – Two types: Intent requirement & Conditional requirements which are used to control the flow.

Route Groups – If many pages have a common set of routes, then we can define route groups and use them in the required pages.

Example – Digital Human –

Revolutionize customer experiences with scalable human connections