はじめに
対話型AIプラットフォーム
チャットボットの概要
自然言語処理(NLP)
ボットの概念と用語
クイックスタートガイド
プラットフォームへのアクセス
ボットビルダーの操作
リリースノート
最新バージョン(英語)
以前のバージョン(英語)
廃止機能(英語)
コンセプト
設計
ストーリーボード
ダイアログタスク
ダイアログタスクとは
ダイアログビルダー
ノードタイプ
インテントノード
ダイアログノード
エンティティノード
フォームノード
確認ノード
ロジックノード
ボットアクションノード
サービスノード
Webhookノード
スクリプトノード
グループノード
エージェント転送ノード
ユーザープロンプト
音声通話プロパティ
イベント ハンドラー
ナレッジグラフ
ナレッジグラフの抽出
ナレッジグラフの構築
ボットにナレッジグラフを追加
グラフの作成
ナレッジグラフの構築
既存のソースからFAQを構築
通知タスク
スモールトーク
デジタルスキル
デジタルフォーム
デジタルビュー
デジタルビューとは
パネル
ウィジェット
トレーニング
トレーニングとは
機械学習
機械学習とは
モデル検証
ファンダメンタルミーニング
ナレッジグラフ
示唆
ランキングおよび解決
NLPの詳細設定
NLPのガイドライン
インテリジェンス
インテリジェンスとは
コンテキスト
コンテキストインテント
割り込み
複数インテントの検出
エンティティの変更
デフォルトの会話
センチメント管理
トーン分析
テストとデバッグ
ボットと会話
発話テスト
バッチテスト
会話テスト
デプロイ
チャネル
公開
分析
ボットの分析
NLPメトリクス
会話フロー
Usage Metrics
封じ込め測定
カスタムダッシュボード
カスタムダッシュボードとは
メタタグ
カスタムダッシュボードとウィジェット
LLM and Generative AI
Introduction
LLM Integration
Kore.ai XO GPT Module
Prompts & Requests Library
Co-Pilot Features
Dynamic Conversations Features
ユニバーサルボット
ユニバーサルボットとは
ユニバーサルボットの定義
ユニバーサルボットの作成
ユニバーサルボットのトレーニング
ユニバーサルボットのカスタマイズ
他言語の有効化
ストア
プラントと使用
Overview
Usage Plans
Support Plans
Invoices
管理
ボット認証
複数言語対応ボット
個人を特定できる情報の編集
ボット変数の使用
IVRのシステム連携
一般設定
ボット管理
ハウツー
会話スキルの設計
バンキングボットを作成
バンキングボット – 資金の振り替え
バンキングボット – 残高を更新
ナレッジグラフを構築
スマートアラートの予約方法
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
デジタルスキルの設計
デジタルフォームの設定方法
デジタルビューの設定方法
データテーブルのデータの追加方法
データテーブルのデータの更新方法
Add Data from Digital Forms
ボットのトレーニング
示唆の使用方法
インテントとエンティティのパターンの使用方法
コンテキスト切り替えの管理方法
ボットのデプロイ
エージェント転送の設定方法
ボット関数の使用方法
コンテンツ変数の使用方法
グローバル変数の使用方法
ボットの分析
カスタムダッシュボードの作成方法
カスタムタグを使ってフィルタリング
Data
Overview
Data Table
Table Views
App Definitions
Data as Service
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
Migrate External Bots
Google Dialogflow Bot
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
Tutorials
BotKit - Blue Prism
BotKit - Flight Search Sample VA
BotKit - Agent Transfer
  1. ホーム
  2. Docs
  3. Process Apps
  4. How To Articles
  5. How to Pass Meta-information During Agent Transfer

How to Pass Meta-information During Agent Transfer

As part of your Virtual Assistant design, you can choose the scenarios where you want to hand off the conversation to human agents. As part of this hand-off, it is important to pass the current conversation context to the Agent Hand-off / CCaaS system. This information can be used in the CCaaS system to set the requisite skills, routing rules, and so on.

The XO Platform offers an extensible framework for handling agent transfer conversations. Within this framework, you can pass any additional metadata you want to share with the agent. This capability allows agents to access supplementary information about the user’s details or queries in advance, enabling them to handle the conversation more efficiently.

How this works

  • The XO platform has introduced a new agent metadata object. This metadata object is currently supported for ServiceNow and Genesys agent integrations, with each integration having its own dedicated metadata object. The naming conventions for these metadata objects are as follows:
    • ServiceNow Agent: “ServiceNowMetaData”
    • Genesys Agent: “GenesysMetaData”
  • The XO platform offers a built-in utility function called “agentUtils.setMetaInfo” to facilitate the exchange of additional information with the agent metadata context object. Developers are expected to leverage this function to set any supplementary data they wish to share with the agent.
  • This function can be utilized anywhere the platform allows the definition of JavaScript code, providing developers with flexibility in integrating custom metadata at various points within the conversational flow.

Set the additional information in the metadata object

  • Before the agent transfer node gets executed in the platform, you need to set the additional information in the metadata object.
  • For example, if you want to set the employee’s “Employee ID” and “Department” in the metadata, a script can be used to set the information in the context, as shown in the screenshot below.

  • The values from the context can be used to set the metadata.
    • For example, if you have collected employee data using entities and wish to pass the gathered entity values to the agent system, you can dynamically define the values by leveraging the entity information available within the context object.
let metaData = {
“EmployeeID”: context.entities.EmployeeID
“Department”: context.entities.Department
}
agentUtils.setMetaInfo("GenesysMetaData", JSON.stringify(memberInfo))

How to access the Metadata in the Genesys agent

As part of the Genesys Bot connector setup, you need to make Get and Set the participant data that needs to be transferred to the agent. The metadata shared by you will be available in the form of attributes in the Genesys agent system. Then you need to set the attributes that need to be shared with the agent using the “SetParticipantData” action in the Genesys bot connector before transitioning to the “ Transfer to ACD” action.

Follow these steps:

  1. In the Genesys agent, click Add attribute in the “SetParticipantData” settings and provide the Key-value pairs that are passed as part of the metadata.
  2. Click Save and then click Publish.

  3. Once the agent transfer call is initiated, the additional metadata is available to the agent at Performance > Workspace > Interactions > Interaction Selected > Participant Data.

How to Pass Meta-information During Agent Transfer

As part of your Virtual Assistant design, you can choose the scenarios where you want to hand off the conversation to human agents. As part of this hand-off, it is important to pass the current conversation context to the Agent Hand-off / CCaaS system. This information can be used in the CCaaS system to set the requisite skills, routing rules, and so on.

The XO Platform offers an extensible framework for handling agent transfer conversations. Within this framework, you can pass any additional metadata you want to share with the agent. This capability allows agents to access supplementary information about the user’s details or queries in advance, enabling them to handle the conversation more efficiently.

How this works

  • The XO platform has introduced a new agent metadata object. This metadata object is currently supported for ServiceNow and Genesys agent integrations, with each integration having its own dedicated metadata object. The naming conventions for these metadata objects are as follows:
    • ServiceNow Agent: “ServiceNowMetaData”
    • Genesys Agent: “GenesysMetaData”
  • The XO platform offers a built-in utility function called “agentUtils.setMetaInfo” to facilitate the exchange of additional information with the agent metadata context object. Developers are expected to leverage this function to set any supplementary data they wish to share with the agent.
  • This function can be utilized anywhere the platform allows the definition of JavaScript code, providing developers with flexibility in integrating custom metadata at various points within the conversational flow.

Set the additional information in the metadata object

  • Before the agent transfer node gets executed in the platform, you need to set the additional information in the metadata object.
  • For example, if you want to set the employee’s “Employee ID” and “Department” in the metadata, a script can be used to set the information in the context, as shown in the screenshot below.

  • The values from the context can be used to set the metadata.
    • For example, if you have collected employee data using entities and wish to pass the gathered entity values to the agent system, you can dynamically define the values by leveraging the entity information available within the context object.
let metaData = {
“EmployeeID”: context.entities.EmployeeID
“Department”: context.entities.Department
}
agentUtils.setMetaInfo("GenesysMetaData", JSON.stringify(memberInfo))

How to access the Metadata in the Genesys agent

As part of the Genesys Bot connector setup, you need to make Get and Set the participant data that needs to be transferred to the agent. The metadata shared by you will be available in the form of attributes in the Genesys agent system. Then you need to set the attributes that need to be shared with the agent using the “SetParticipantData” action in the Genesys bot connector before transitioning to the “ Transfer to ACD” action.

Follow these steps:

  1. In the Genesys agent, click Add attribute in the “SetParticipantData” settings and provide the Key-value pairs that are passed as part of the metadata.
  2. Click Save and then click Publish.

  3. Once the agent transfer call is initiated, the additional metadata is available to the agent at Performance > Workspace > Interactions > Interaction Selected > Participant Data.
メニュー