GETTING STARTED
Kore.ai XO Platform
Virtual Assistants Overview
Natural Language Processing (NLP)
Concepts and Terminology
Quick Start Guide
Accessing the Platform
Navigating the Kore.ai XO Platform
Building a Virtual Assistant
Help & Learning Resources
Release Notes
Current Version
Recent Updates
Previous Versions
Deprecations
Request a Feature
CONCEPTS
Design
Storyboard
Overview
FAQs
Conversation Designer
Overview
Dialog Tasks
Mock Scenes
Dialog Tasks
Overview
Navigate Dialog Tasks
Build Dialog Tasks
Node Types
Overview
Intent Node
Dialog Node
Dynamic Intent Node
GenAI Node
GenAI Node (v2, BETA)
GenAI Prompt
Entity Node
Form Node
Confirmation Node
Message Nodes
Logic Node
Bot Action Node
Service Node
Webhook Node
Script Node
Process Node
Agent Transfer
Node Connections
Node Connections Setup
Sub-Intent Scoping
Entity Types
Entity Rules
User Prompts or Messages
Voice Call Properties
Knowledge AI
Introduction
Knowledge Graph
Introduction
Terminology
Build a Knowledge Graph
Manage FAQs
Knowledge Extraction
Import or Export Knowledge Graph
Prepare Data for Import
Importing Knowledge Graph
Exporting Knowledge Graph
Auto-Generate Knowledge Graph
Knowledge Graph Analysis
Answer from Documents
Alert Tasks
Small Talk
Digital Skills
Overview
Digital Forms
Digital Views
Introduction
Widgets
Panels
Session and Context Variables
Context Object
Intent Discovery
Train
NLP Optimization
ML Engine
Overview
Model Validation
FM Engine
KG Engine
Traits Engine
Ranking and Resolver
Training Validations
NLP Configurations
NLP Guidelines
LLM and Generative AI
Introduction
LLM Integration
Kore.ai XO GPT Module
Prompts & Requests Library
Co-Pilot Features
Dynamic Conversations Features
Guardrails
Intelligence
Introduction
Event Handlers
Contextual Memory
Contextual Intents
Interruption Management
Multi-intent Detection
Amending Entities
Default Conversations
Conversation Driven Dialog Builder
Sentiment Management
Tone Analysis
Default Standard Responses
Ignore Words & Field Memory
Test & Debug
Overview
Talk to Bot
Utterance Testing
Batch Testing
Conversation Testing
Conversation Testing Overview
Create a Test Suite
Test Editor
Test Case Assertion
Test Case Execution Summary
Glossary
Health and Monitoring
NLP Health
Flow Health
Integrations
Actions
Actions Overview
Asana
Configure
Templates
Azure OpenAI
Configure
Templates
BambooHR
Configure
Templates
Bitly
Configure
Templates
Confluence
Configure
Templates
DHL
Configure
Templates
Freshdesk
Configure
Templates
Freshservice
Configure
Templates
Google Maps
Configure
Templates
Here
Configure
Templates
HubSpot
Configure
Templates
JIRA
Configure
Templates
Microsoft Graph
Configure
Templates
Open AI
Configure
Templates
Salesforce
Configure
Templates
ServiceNow
Configure
Templates
Stripe
Configure
Templates
Shopify
Configure
Templates
Twilio
Configure
Templates
Zendesk
Configure
Templates
Agents
Agent Transfer Overview
Custom (BotKit)
Drift
Genesys
Intercom
NiceInContact
NiceInContact(User Hub)
Salesforce
ServiceNow
Configure Tokyo and Lower versions
Configure Utah and Higher versions
Unblu
External NLU Adapters
Overview
Dialogflow Engine
Test and Debug
Deploy
Channels
Publishing
Versioning
Analyze
Introduction
Dashboard Filters
Overview Dashboard
Conversations Dashboard
Users Dashboard
Performance Dashboard
Custom Dashboards
Introduction
Custom Meta Tags
Create Custom Dashboard
Create Custom Dashboard Filters
LLM and Generative AI Logs
NLP Insights
Task Execution Logs
Conversations History
Conversation Flows
Conversation Insights
Feedback Analytics
Usage Metrics
Containment Metrics
Universal Bots
Introduction
Universal Bot Definition
Universal Bot Creation
Training a Universal Bot
Universal Bot Customizations
Enabling Languages
Store
Manage Assistant
Team Collaboration
Plan & Usage
Overview
Usage Plans
Templates
Support Plans
Invoices
Authorization
Conversation Sessions
Multilingual Virtual Assistants
Get Started
Supported Components & Features
Manage Languages
Manage Translation Services
Multiingual Virtual Assistant Behavior
Feedback Survey
Masking PII Details
Variables
Collections
IVR Settings
General Settings
Assistant Management
Manage Namespace
Data
Overview
Guidelines
Data Table
Table Views
App Definitions
Data as Service
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
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
Rate Limits
API List
koreUtil Libraries
SDK Reference
SDK Introduction
Web SDK
How the Web SDK Works
SDK Security
SDK Registration
Web Socket Connect and RTM
Tutorials
Widget SDK Tutorial
Web SDK Tutorial
BotKit SDK
BotKit SDK Deployment Guide
Installing the BotKit SDK
Using the BotKit SDK
SDK Events
SDK Functions
Installing Botkit in AWS
Tutorials
BotKit - Blue Prism
BotKit - Flight Search Sample VA
BotKit - Agent Transfer

ADMINISTRATION
Intro to Bots Admin Console
Administration Dashboard
User Management
Managing Your Users
Managing Your Groups
Role Management
Manage Data Tables and Views
Bot Management
Enrollment
Inviting Users
Sending Bulk Invites to Enroll Users
Importing Users and User Data
Synchronizing Users from Active Directory
Security & Compliance
Using Single Sign-On
Two-Factor Authentication for Platform Access
Security Settings
Cloud Connector
Analytics for Bots Admin
Billing
  1. Home
  2. Docs
  3. Virtual Assistants
  4. What's New
  5. What’s New

What’s New

Learn about the new features and enhancements included in Kore.ai Experience Optimization Platform v10.2, released on April 27, 2024.

Key features and enhancements included in this release are summarized below.

LLM and Generative AI

Custom LLM Integration Support for Rephrase Dialog Responses

Rephrase Dialog Responses now supports Custom LLMs in addition to commercial LLMs. This allows platform users to use the rephrasing feature with their own custom-trained language models and create customized prompts tailored to their specific use cases, models, and linguistic contexts, providing greater flexibility and control over the rephrasing process and conversational experiences. Learn more.

NLP

New Pre-trained MPNet Few-shot Model for Intent Detection

The few-shot model now supports the Pre-trained MPNet embedding model for intent detection. The Pre-trained MPNet model is the advanced version of MPNet. It has been pre-trained and fine-tuned for superior accuracy and precision in intent identification compared to MPNet. Learn more.

Advantages of using the Pre-trained MPNet Model:

  • Understanding Negations: Pre-trained models get negations like “not” or “don’t” easily, unlike MPNet, which might mix things up. So, when you say, “I want to transfer funds,” and “I do not want to transfer funds,” pre-trained models know the difference, making them better at understanding what you really mean.
  • Clear Intent Differentiation: Pre-trained models are great at telling apart similar things, which can be tricky for MPNet. For example, if you say, “I want to unblock a card,” or “I want to block a card,” pre-trained models can confidently tell the difference between wanting to block or unblock a card, unlike MPNet, which might get confused.
  • Staying on Topic: Pre-trained models are good at sticking to the topic at hand. So, if you talk about increasing your credit card limit, they won’t start suggesting things unrelated to credit cards, unlike MPNet, which might go off track.
  • Easier Training: Pre-trained models need less training data compared to MPNet. This means the model can learn the same things with fewer examples, making the training process faster and simpler.

Channels

Support for Thread Handling for Virtual Assistants in Slack Channels

The Platform now offers native support for threaded conversations in the Slack channel. Users can initiate a new thread from any message within a Slack channel or direct message group.

Additionally, the platform provides extended functionality for developers. It can automatically create a new thread whenever a user @mentions the virtual assistant in a Slack channel. This behavior is configurable, giving developers control over this feature.

Digital Forms

  • Enable the “Off-the-Record Information” Flag for Digital Forms: On a digital form, when the field’s “Off the record” flag is enabled, the field data is cleared at the end of the user session and not stored in databases or logs.
  • Digital Forms Date Picker Supports Japanese: The digital form’s Date Picker now supports the Japanese language if the bot language is Japanese.

What’s New

Learn about the new features and enhancements included in Kore.ai Experience Optimization Platform v10.2, released on April 27, 2024.

Key features and enhancements included in this release are summarized below.

LLM and Generative AI

Custom LLM Integration Support for Rephrase Dialog Responses

Rephrase Dialog Responses now supports Custom LLMs in addition to commercial LLMs. This allows platform users to use the rephrasing feature with their own custom-trained language models and create customized prompts tailored to their specific use cases, models, and linguistic contexts, providing greater flexibility and control over the rephrasing process and conversational experiences. Learn more.

NLP

New Pre-trained MPNet Few-shot Model for Intent Detection

The few-shot model now supports the Pre-trained MPNet embedding model for intent detection. The Pre-trained MPNet model is the advanced version of MPNet. It has been pre-trained and fine-tuned for superior accuracy and precision in intent identification compared to MPNet. Learn more.

Advantages of using the Pre-trained MPNet Model:

  • Understanding Negations: Pre-trained models get negations like “not” or “don’t” easily, unlike MPNet, which might mix things up. So, when you say, “I want to transfer funds,” and “I do not want to transfer funds,” pre-trained models know the difference, making them better at understanding what you really mean.
  • Clear Intent Differentiation: Pre-trained models are great at telling apart similar things, which can be tricky for MPNet. For example, if you say, “I want to unblock a card,” or “I want to block a card,” pre-trained models can confidently tell the difference between wanting to block or unblock a card, unlike MPNet, which might get confused.
  • Staying on Topic: Pre-trained models are good at sticking to the topic at hand. So, if you talk about increasing your credit card limit, they won’t start suggesting things unrelated to credit cards, unlike MPNet, which might go off track.
  • Easier Training: Pre-trained models need less training data compared to MPNet. This means the model can learn the same things with fewer examples, making the training process faster and simpler.

Channels

Support for Thread Handling for Virtual Assistants in Slack Channels

The Platform now offers native support for threaded conversations in the Slack channel. Users can initiate a new thread from any message within a Slack channel or direct message group.

Additionally, the platform provides extended functionality for developers. It can automatically create a new thread whenever a user @mentions the virtual assistant in a Slack channel. This behavior is configurable, giving developers control over this feature.

Digital Forms

  • Enable the “Off-the-Record Information” Flag for Digital Forms: On a digital form, when the field’s “Off the record” flag is enabled, the field data is cleared at the end of the user session and not stored in databases or logs.
  • Digital Forms Date Picker Supports Japanese: The digital form’s Date Picker now supports the Japanese language if the bot language is Japanese.
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