GETTING STARTED
Kore.ai XO Platform
Virtual Assistants Overview
Natural Language Processing (NLP)
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Quick Start Guide
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Building a Virtual Assistant
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CONCEPTS
Design
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Supported Company Names
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Knowledge Graph
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Knowledge Extraction
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Digital Skills
Overview
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Introduction
Overview Dashboard
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Introduction
Custom Meta Tags
Create Custom Dashboard
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Smart Bots
Universal Bots
Introduction
Universal Bot Definition
Universal Bot Creation
Training a Universal Bot
Universal Bot Customizations
Enabling Languages
Store
Manage Assistant
Plan & Usage
Overview
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Invoices
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Multilingual Virtual Assistants
Get Started
Supported Components & Features
Manage Languages
Manage Translation Services
Multiingual Virtual Assistant Behavior
Masking PII Details
Variables
Collections
IVR Settings
General Settings
Assistant Management
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Data as Service
Data Table
Table Views
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HOW TOs
Build a Travel Planning Assistant
Travel Assistant Overview
Create a Travel Virtual Assistant
Design Conversation Skills
Create an ‘Update Booking’ Task
Create a Change Flight Task
Build a Knowledge Graph
Schedule a Smart Alert
Design Digital Skills
Configure Digital Forms
Configure Digital Views
Train the Assistant
Use Traits
Use Patterns
Manage Context Switching
Deploy the Assistant
Configure Agent Transfer
Use Bot Functions
Use Content Variables
Use Global Variables
Use Web SDK
Build a Banking Assistant
Design Conversation Skills
Create a Sample Banking Assistant
Create a Transfer Funds Task
Create a Update Balance Task
Create a Knowledge Graph
Set Up a Smart Alert
Design Digital Skills
Configure Digital Forms
Configure Digital Views
Add Data to Data Tables
Update Data in Data Tables
Add Data from Digital Forms
Train the Assistant
Composite Entities
Use Traits
Use Patterns for Intents & Entities
Manage Context Switching
Deploy the Assistant
Configure an Agent Transfer
Use Assistant Functions
Use Content Variables
Use Global Variables
Intent Scoping using Group Node
Analyze the Assistant
Create a Custom Dashboard
Use Custom Meta Tags in Filters
APIs & SDKs
API Reference
API Introduction
API List
API Collection
koreUtil Libraries
SDK Reference
SDK Introduction
SDK Security
SDK Registration
Web Socket Connect and RTM
Using the BotKit SDK
BotKit SDK Tutorial - Blue Prism
Widget SDK Tutorial
Web SDK Tutorial
ADMINISTRATION
Introduction to Admin Console
Administration Dashboard
User Management
Add Users
Manage Groups
Manage Roles
Assistant Management
Enrollment
Invite Users
Send Bulk Invites
Import User Data
Synchronize Users from AD
Security & Control
Using Single-Sign On
Security Settings
Cloud Connector
Analytics
Billing
  1. Home
  2. Docs
  3. Virtual Assistants
  4. Advanced Topics
  5. Universal Bot
  6. Universal Bots

Universal Bots

Kore.ai’s Universal Bots facilitate a scalable, modular approach to Bot building by helping you link several Bots into one.

Universal Bot is a container bot that can be linked with one or more Standard Bots. When a user interacts with the Universal Bots, it routes the user utterance to the appropriate linked bot for intent detection or task fulfillment.

Note: A universal Bot doesn’t own the linked bots, but it interprets the user utterances and maps them to the correct linked bots. The changes that you make to a linked bot task from inside the universal bot, such as training the task, are saved directly to the linked bot. Also, you cannot create any task for the universal bots except for customizing a default dialog task that gets created automatically with every universal bot.

Highlights

  • The universal bot acts as a single interface for the Bot users of an enterprise, across business lines or products or services.
  • Standard bots that aim to meet a specific purpose can be built independently and then be associated with a Universal bot by linking them to the Universal Bot.
  • The developer can view and analyze all user interactions from within the Universal bot and also train the respective bots with additional training data.
  • The developer can train the Universal bot for identifying the relevant bots from a user utterance, using the ranking and disambiguation model. Universal Bot can be trained in three aspects:
    • Using example utterances like the Machine Learning model. This would help identify a set of linked bots as possible matches to the user utterance.
    • Invocation Names that would identify a specific linked bot from the user utterance.
    • Invocation Phrases that would identify a specific intent in a specific bot from the user utterance.
      Refer here to know more about training a Universal Bot.
  • This trained Universal Bot can then be published so that when the end-users interact with Universal bot, it will perform intent recognition across all linked bots to understand the user’s intent and engage the appropriate bot to perform the task.
  • In the case of ambiguity in identifying an appropriate bot or task, a sub-dialog is initiated to obtain confirmation from the user.
  • Universal bots also provide a  Fallback Bot for gracefully handling any untrained/un-recognized requests.
  • Linked bots can be marked as Inclusive bots that need not be trained with sample utterances to participate in the bot scoping process (introduced in ver8.0).
  • Apart from this, the developer can define eligible bots ie. assign specific bots to specific end-users so that only the intents from these bots are made available to them.

Implementation

The following flow chart shows the working of a Universal bot:

The following is the explanation for the above process flow:

  • Universal Bot checks id any eligible bots are defined.
  • If defined, then the list of eligible bots is obtained, else the user intent is checked against any Small Talk, etc.
  • If eligible bots not defined then all the linked bots are considered as eligible.
  • Once the linked eligible bots list is there, Universal Bot identifies the bots that qualify using the invocation phrases. (See the bot training page for details)
  • The user utterance is sent to the scoped bots and the results are processed by the Universal Bot’s Ranking and Resolver engine.

Universal Bot – upgrade

Post ver7.3 release of the platform, new Universal Bots would be versioned as 2.0.

We recommend you upgrade since the older version of universal bot will be deprecated soon. The previous version of Universal bot has the following limitations:

  • Training – you cannot train the universal bot, need to depend upon the training of the linked bots for proper functioning.
  • There are performance issues with the older version if the number of linked bots exceeds 5 or the total number of intents exceeds 100.
  • Variable Management is not possible from the older version of Universal bot.

Older version universal bots will prompt you to Upgrade when:

  • you open the universal bot; or
  • when from the left navigation menu you access Natural Language -> Training.

Once you upgrade, follow these steps to ensure that the user utterances are routed to the relevant linked bots:

  • Train the Universal Bot to identify the linked bots by providing Training Utterances or Invocation Names. The Universal Bot will route the user utterances only to the identified linked bots.
  • Mark linked bots as Fallback Bots. The utterances are routed to the Fallback bots when no other linked bots are qualified from the training provided. A maximum of 15 linked bots can be marked as Fallback bots.
  • Review the linked bot identification flow from the Utterance Testing module.

Refer here for more on training the Universal Bot.

Next Steps

  • Know more about Universal Bots and compare with Standard Bots behavior from here.
  • You can also start creating your Universal Bots by referring here.
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