User Guide
eva 3.4.1
eva 3.4.1
  • Home and Support
  • What's new
  • Changelog
  • Using eva
    • Overview
      • Virtual Agents
      • Main Concepts of eva
      • Glossary
    • Developing virtual agents
      • Quick Start with eva
      • Dialog Flows
      • Dialog Cells
        • Intent Cells
        • Entity Cells
        • Answer Cells
        • Service Cells
        • Input Cells
        • Jump Cells
        • End Cells
        • Code Cells
        • Rule Cells
      • Training task
      • Export and import agents
      • Create virtual agents from templates
      • Create and manage users
    • Channels
      • Integrating Existing Channels
    • Testing Virtual Agents
      • Test a virtual agent
      • Automated Test
    • Natural Language
      • eva NLP
      • Training with eva NLP
      • Training with eva Automated Learning
      • Using other NLP engines
    • Analytics
      • External analytics platforms
    • Experience
      • Context Management
    • Advanced Options
      • Parameters
      • Intent Navigator
      • PII Data masking
    • How Tos
      • Creating variable answers with Code and Rule cells
      • Videos
  • for technicians
    • eva server Installation guide
    • API Guidelines
      • Conversation API
      • Cloner API
      • Webhooks
    • Supported/verified third-party software
    • Appendices
    • Data Extraction
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On this page
  • Main concepts
  • Dialog Manager
  • Workspace
  • Dialog Cells
  • Intent cell
  • Entity cell
  • Answer cell
  • Jump cell
  • Service cell
  • Input cell
  • End cell
  • Code cell
  • Rule cell
  • Conversational Flows
  1. Using eva
  2. Overview

Main Concepts of eva

A summary of eva's features is ranked in order of importance.

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Last updated 2 years ago

Main concepts

In a nutshell, everything you need to build a virtual agent has included in NTT Data eva conversational AI.

Dialog Manager

The Dialog Manager is the main feature, the canvas where you create the dialogs and build your virtual agent knowledge base.

The Dialog Manager has 7 main sections:

  1. Workspace

  2. Flows

  3. Intents

  4. Entities

  5. Services

  6. Answers

  7. Training (if you are using eva NLP)

More information:

Workspace

The workplace is the first and the main tab of Dialog Manager since it is the area where it is possible to view and also design the flows.

The Workspace is where you will build your virtual agent knowledge base. Here, you will create cells and string them together to form flows.

Dialog Cells

Conversational flows are composed of a set of elements called cells that work in an orchestrated way. There are different types of cells, and they are used for different purposes within the flow. Specific purpose.

Using the workplace, eva guides you for the development of the logic of the flows.

There are many types of cells:

Intent cell

When designing a conversational flow you need to predict the user interactions and the virtual agent responses.

An intent cell will represent the users' interactions. It is the representation of a user's will, in other words, an action.

Usually it is associated with a verb. For example, when the user says he wants to buy something he is expressing a will, that is, an intention.

Since users can express the same will in different ways, the intention cell is composed of examples. The examples are all the possible ways the user can express the same will.

Examples of a purchase intention:

  • I want to buy

  • I want to acquire

  • I want to make a purchase

Entity cell

Entities represents a user interaction, but unlike the Intent, it is usually associated with an adjective, noun, product, services, etc. In most cases, entities complement intentions.

For example, if the the user says: "I want to buy an Apple phone"

The terms "cell phone" and "Apple" will be Entities, because they represent a product and a brand.

Entities can also represent a very specific user interaction, such as an email. In cases where it is impossible to map all possible user interactions, such as an email list, we design a standardized term that will cater for this type of interaction. And for this we use standard type entity.

Answer cell

As the name suggests, the Answer cell will bring a virtual agent's feedback to a user's input.

In eva, you can also make your response evaluable. In the bottom corner, you can put a thumbs up and a thumbs down. This way you will know whether the user's feedback was positive or negative.

eva has six types of responses:

1) Simple Answers: the virtual agent predicts answers to user questions

b) Not Expected Answers: the answer given by the virtual agent to an unidentified user demand

c) FAQ: flows built based on answers to intentions

d) Dynamic Answers: through simple codes, brings personalized answers

e) Transactional Answers: when the answer will depend on an API

f) Channel-based Responses: responses that vary according to the channels

Jump cell

As the name suggests, the Jump function allows you to go from the last cell created to any other cell in any flow.

This is perfect to avoid repetition, as well as shortening and simplifying flows.

Service cell

Often, a response to a user demand will require information that will necessarily be outside the eva, on other servers.

For example, informing a customer's balance, credit card account, closing a purchase on an ecommerce virtual agent, etc.

Here comes the Service cell, which connects the user to eva and the customer.

In it, there is a field to put Webhook. If you have never heard of this expression, it is a protocol used so that an application (APP) on the internet receives real-time information as soon as an event occurs in another web-based application.

Input cell

"What is your birth date?", "write your name here", "put your account number here". The Input cell will be responsible for storing this information in the eva.

There are three types:

a) Date Template: allows the insertion of dates.

b) Time Template: allows the insertion of time (hour and minutes)

c) Customizable templates: you can enter locations, zip codes, among other data

End cell

The End Cell works like an end point in a flow. By placing this feature, the virtual agent stops communicating at that point. That is, it will only resume the dialog if the user (the virtual agent's interlocutor) interacts again.

The End Cell is always used in a Jump flow, never in the User Journey (the main one).

Code cell

The Code Cell allows you to perform some services without relying on APIs. It offers immense advantages in a flow.

Through the Code Cell it is possible to

  • Manipulate objects

  • Anticipate executions and actions

  • Perform services without the need for APIs

  • Reduce time and cost

Rule cell

Imagine two users that have the same intention: checking their bank balance. However, one is already logged into the bank and the other is not. In cases like this, the Rule Cell comes in, to steer each user in the right direction.

This is a feature to make your dialog more assertive and much more precise, especially when Intentions and Entities can bring up multiple scenarios.

The language used is JavaScript.

Conversational Flows

When you connect Intents, Entities and Answers, you form a flow.

A virtual agent probably will have more than one flow.

Developing virtual agents
Learn more about intents
Learn more about entities
Learn more about answers
Learn more about jump cells
Learn more about service cell
Learn more about input cells
Learn more about end cells
Learn more about code cells
Learn more about rule cells
Learn more about flows
eva components diagrams