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 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
Intelligence
Introduction
Event Handlers
Contextual Memory
Contextual Intents
Interruption Management
Multi-intent Detection
Amending Entities
Default Conversations
Conversation Driven Dialog Builder
Sentinment 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
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
Migrate External Bots
Google Dialogflow Bot
APIs & SDKs
API Reference
API Introduction
Rate Limits
API List
koreUtil Libraries
SDK Reference
SDK Introduction
SDK Security
SDK Registration
Web Socket Connect and RTM
Installing the BotKit SDK
Using the BotKit SDK
SDK Events
SDK Functions
SDK Tutorials
BotKit - Blue Prism
BotKit - Flight Search Sample VA
BotKit - Agent Transfer
Widget SDK Tutorial
Web SDK Tutorial
ADMINISTRATION
Introduction to Admin Console
Administration Dashboard
User Management
Add Users
Manage Groups
Manage Roles
Data Tables and Views
Assistant Management
Enrollment
Invite Users
Send Bulk Invites
Import User Data
Synchronize Users from AD
Security & Control
Using Single-Sign On (SSO)
Two-Factor Authentication (2FA)
Security Settings
Cloud Connector
Analytics
Billing
  1. Home
  2. Docs
  3. Virtual Assistants
  4. API Guide
  5. Get Analytics API

Get Analytics API

The Get Analytics API allows you to retrieve metrics data related to intent detection and task performance. The API provides information about various metrics, including Intents Found, Intents not Found, Unhandled Utterances, Failed Tasks, Successful Tasks, and Performance Logs.

Method POST
Endpoint https://{{host}}/api/public/bot/{{BotID}}/getAnalytics
Content Type application/json
Authorization auth: {{JWT}}

See How to generate the JWT Token.

API Scope
  • Bot Builder: Metrics
  • Admin Console: Not Applicable

Path Parameters

Parameter Required/Optional Description
host Required Environment URL, for example, https://bots.kore.ai
BotID Required Bot ID or Stream ID. You can access it from the General Settings page of the bot.

Sample Request

The following sample request shows how to retrieve unhandled utterance analytics data with specific filters. You can modify the type and filters parameters to retrieve different types of analytics data as needed.

curl --location --request POST 'https://bots.kore.ai/api/public/bot/st-xxxxxxd-xxxx-xxxx-xxxx-xxxxxxxxxx/getAnalytics' \
--header 'auth: {{YOUR_JWT_ACCESS_TOKEN}}' \
--header 'content-type: application/json' \
--data-raw '{
    "type": "unhandledutterance",
    "filters": {
        "from": "2022-09-11T17:25:09.698Z",
        "to": "2022-09-25T17:25:09.698Z",
       
           
        "channel": [
            "rtm"
        ],
        "isAmbiguous": false,
        "isDeveloper": false,
        "trained": false,
        "userId": [
            "u-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxx"
        ]
       
       
    },
    "sort":
        { "order": "asc",
          "by": "nodeName" },
   
    "limit": 50
}'

Request Body Parameters

Parameter Type Description
type string, required Indicates the type of metrics for which you can retrieve data:

  • successintent
  • failintent
  • successtask
  • failtask
  • performance
  • unhandledutterance
filters object, required A set of filters to narrow down the analytics data.
filters.from string, required The start timestamp for the data retrieval.
filters.to string, required The end timestamp for the data retrieval.
filters.channel array of strings, optional An array containing channel names to filter data by; the default channel is “rtm”.

Accepted channels are:

  • “skypeforbusiness”
  • “msteams”
  • “twitter”
  • “spark”
  • “rtm”
  • “facebook”
  • “slack”
  • “skype”
  • “kore”
  • “email”
  • “sms”
  • “facebook”
  • “ringcentral”
  • “jabber”
  • “yammer”
  • “alexa”
  • “twiliovoice”
  • “telegram”
  • “ivr”
  • “ivrVoice”
  • “smartassist”
  • “line”
  • “liveperson”
  • “googleactions”
  • “hangoutchat”
  • “mattermost”
  • “rcs”
filters.channel.channelUIds array of strings, optional The end-user’s identity provided by the channel.

Note: For “ivr” channel, it’s a combination of {accountId}/{channel}/{channelUId}.
For example,
"channelUIds": ["5fb6a04e20ab9d2c19cb73xx/ivrinst-893b4d4f-1fc1-54c3-b3xx-fa7200c4c2xx/first.last@domain.com"]

filters.isAmbiguous boolean, optional Whether to include ambiguous intents or not – set to true or false.
filters.isDeveloper boolean, optional Whether to include developer metrics – set to true or false.
filters.trained boolean, optional Whether to include trained intents or not – set to true or false.
filter.taskId array of strings, optional To filter based on the task IDs.
filters.userId array of strings, optional To filter based on user IDs.
filters.tags object, optional Meta tags to filter the records.
Usage example:

"tags": {
         "and": [
                 {
                  "name": "user",
                  "values": ["uservalue"],
                  "type": "user"
                  },
                  {
                   "name": "message",
                   "values": ["mvalue"],
                   "type": "message"
                   }
                ]
           }
sort object, optional An object containing the sorting criteria to apply to the data being retrieved:

  • order (string, required): Sorting order, either “asc” for ascending or “desc” for descending.
  • by (string, required): The field/column by which the data should be sorted.

Usage example:

"sort": 
       { "order": "<desc/asc>", 
          "by": "<column name>" }
limit integer, required Indicates the number of records to be returned in the result set.
skip integer, required The number of records to be skipped from the result set.

Sample Response

{
    "moreAvailable": false,
    "result": [
        {
            "_id": "63xxxxxxxxxxxxxxxxx",
            "messageId": "ms-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxx",
            "sessionId": "63xxxxxxxxxxxxxxx",
            "utterance": "aslfkj",
            "intent": "Mobile Enquiry",
            "userId": "u-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxx",
            "channelUId": "test@abc.xyz",
            "language": "en",
            "timestamp": "2022-09-24T08:24:39.840Z",
            "pinned": false,
            "channel": "rtm",
            "winningIntent": [],
            "isAmbiguous": false,
            "ambiguousIntents": [],
            "taskName": "Mobile Enquiry",
            "flow": [],
            "taskId": "dg-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx",
            "koralogstatusId": "f-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxx-xxxxxxxxxxx",
            "customTags": {
                "userTags": [
                    {
                        "name": "Name",
                        "value": "John"
                    }
                ],
                "sessionTags": [],
                "messageTags": []
            },
            "NLAnalysis": {
                "result": "unhandledUtterance",
                "messageStoreId": "ms-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxx",
                "channelId": "st-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxx:u-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxx:rtm",
                "bot": "Channel Check",
                "botid": "st-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxx",
                "skipConversation": true,
                "task": "Mobile Enquiry",
                "botLanguage": "en-US",
                "nluLanguage": "en-US",
                "taskId": "dg-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxx",
                "fields": {},
                "logSequenceId": "f-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxx-xxxxxxxxxx",
                "intentStatus": "published",
                "subType": "dialog",
                "channelInfo": "st-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx:u-xxxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx:rtm",
                "input": [
                    "aslfkj"
                ],
                "taskContextId": "dcx-xxxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx",
                "NLAnalysis": {
                    "intentRescoring": true,
                    "isPreferDefinitiveMatch": true,
                    "scoringModel": "original",
                    "toneAnalysis": {},
                    "nlProcessing": {
                        "originalInput": "aslfkj",
                        "spellCorrectedInput": null,
                        "canonical": "Aslak",
                        "wordAnalysis": [
                            {
                                "index": 1,
                                "word": "Aslak",
                                "ignored": false,
                                "pos": "Noun_proper_singular ",
                                "role": "MAINSUBJECT ",
                                "original": "aslfkj",
                                "processedWord": "Aslak"
                            }
                        ]
                    },
                    "ml": {
                        "intentModel": "bot level intent model",
                        "eliminated": [
                            {
                                "task": "Book Appointment",
                                "state": "published",
                                "score": 0.017055602351504544,
                                "scoringCriteria": "Probabilistic score",
                                "matchType": "unlikely"
                            },
                            {
                                "task": "Transfer Money",
                                "state": "published",
                                "score": 0.011911144983740555,
                                "scoringCriteria": "Probabilistic score",
                                "matchType": "unlikely"
                            },
                            {
                                "task": "Show Balance",
                                "state": "published",
                                "score": 0.009209086809082547,
                                "scoringCriteria": "Probabilistic score",
                                "matchType": "unlikely"
                            }
                        ],
                        "namedEntityRecognition": []
                    },
                    "faq": {
                        "demystify": {
                            "lemmatizer_used": "PATTERN",
                            "normalizedQuery": "aslfkj",
                            "OntologyTraits": [],
                            "failed_questions": {},
                            "SelectedPathCount": 3,
                            "ExtractedEntities": [],
                            "ContextEntities": [],
                            "PreConditionNodes": [],
                            "filtered_questions": {
                                "score": [],
                                "traits": []
                            }
                        }
                    }
                },
                "language": "en",
                "channel": "rtm",
                "userId": "u-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx",
                "time": "2022-09-24T08:24:39.808Z",
                "channelclient": "botbuilder",
                "_id": "f-121d2486-xxxx-xxxx-xxxx-xxxxxxxxxx-xxxxxxxxxx",
                "resourceid": "korastatuslogs",
                "entityOrgId": "o-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxx",
                "iv": "VP47awbZ8JRCoqFtgPx7fA==",
                "cek": {
                    "header": {
                        "alg": "dir",
                        "enc": "aes-256-cbc",
                        "kid": "k-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxx"
                    }
                },
                "ire": true
            },
            "nodeName": "Entity_color",
            "promptType": "entity"
        },
        {
            "_id": "63xxxxxxxxxxxx",
            "messageId": "ms-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxx",
            "sessionId": "63xxxxxxxxxxxxxxxxx",
            "utterance": "alskd",
            "intent": "Mobile Enquiry",
            "userId": "u-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxx",
            "channelUId": "ramakrishnakoretest@getnada.com",
            "language": "en",
            "timestamp": "2022-09-24T08:24:50.257Z",
            "pinned": false,
            "channel": "rtm",
            "winningIntent": [],
            "isAmbiguous": false,
            "ambiguousIntents": [],
            "taskName": "Mobile Enquiry",
            "flow": [],
            "taskId": "dg-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx",
            "koralogstatusId": "f-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx-xxxxxxx",
            "customTags": {
                "userTags": [
                    {
                        "name": "Name",
                        "value": "Krishna"
                    }
                ],
                "sessionTags": [],
                "messageTags": []
            },
            "NLAnalysis": {
                "result": "unhandledUtterance",
                "messageStoreId": "ms-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxx",
                "channelId": "st-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxx:u-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx:rtm",
                "bot": "Channel Check",
                "botid": "st-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx",
                "skipConversation": true,
                "task": "Mobile Enquiry",
                "botLanguage": "en-US",
                "nluLanguage": "en-US",
                "taskId": "dg-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx",
                "fields": {},
                "logSequenceId": "f-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx-xxxxxxx",
                "intentStatus": "published",
                "subType": "dialog",
                "channelInfo": "st-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxx:u-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx:rtm",
                "input": [
                    "alskd"
                ],
                "taskContextId": "dcx-b3e58798-ed3b-5f3d-9894-2e26758001eb",
                "NLAnalysis": {
                    "intentRescoring": true,
                    "isPreferDefinitiveMatch": true,
                    "scoringModel": "original",
                    "toneAnalysis": {},
                    "nlProcessing": {
                        "originalInput": "alskd",
                        "spellCorrectedInput": null,
                        "canonical": "alskd",
                        "wordAnalysis": [
                            {
                                "index": 1,
                                "word": "unknown-word",
                                "ignored": false,
                                "pos": "Noun_infinitive Noun_singular Verb_infinitive Verb_present Adjective_normal Adverb ",
                                "original": "alskd",
                                "processedWord": "alskd"
                            }
                        ]
                    },
                    "ml": {
                        "intentModel": "bot level intent model",
                        "eliminated": [
                            {
                                "task": "Book Appointment",
                                "state": "published",
                                "score": 0.017055602351504544,
                                "scoringCriteria": "Probabilistic score",
                                "matchType": "unlikely"
                            },
                            {
                                "task": "Transfer Money",
                                "state": "published",
                                "score": 0.011911144983740555,
                                "scoringCriteria": "Probabilistic score",
                                "matchType": "unlikely"
                            },
                            {
                                "task": "Show Balance",
                                "state": "published",
                                "score": 0.009209086809082547,
                                "scoringCriteria": "Probabilistic score",
                                "matchType": "unlikely"
                            }
                        ],
                        "namedEntityRecognition": []
                    },
                    "faq": {
                        "demystify": {
                            "lemmatizer_used": "PATTERN",
                            "normalizedQuery": "alskd",
                            "OntologyTraits": [],
                            "failed_questions": {},
                            "SelectedPathCount": 3,
                            "ExtractedEntities": [],
                            "ContextEntities": [],
                            "PreConditionNodes": [],
                            "filtered_questions": {
                                "score": [],
                                "traits": []
                            }
                        }
                    }
                },
                "language": "en",
                "channel": "rtm",
                "userId": "u-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxx",
                "time": "2022-09-24T08:24:50.226Z",
                "channelclient": "botbuilder",
                "_id": "f-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxx-xxxxxxxx",
                "resourceid": "korastatuslogs",
                "entityOrgId": "o-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxx",
                "iv": "+Kl5i6AAFJp0g3NkExn+Og==",
                "cek": {
                    "header": {
                        "alg": "dir",
                        "enc": "aes-256-cbc",
                        "kid": "k-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx"
                    }
                },
                "ire": true
            },
            "nodeName": "Entity_capacity",
            "promptType": "entity"
        }
    ],
    "totalCount": 2
}

Response Body Parameters

PARAMETER DESCRIPTION
moreAvailable Indicates if the API has returned all the records or if more are available, based on the pagination criteria.

True if more records are available. False if there are no more records to be retrieved.

result Contains complete information about the metrics.
id The unique identifier for the record.
messagesId The unique identifier for the message record.
sessionId The unique identifier for the session.
utterance The user utterance/input.
intent The identified intent for the user’s utterance/input.
userId The unique identifier for the user.
channelUId The end-user’s identity provided by the channel. It can be the user’s email ID or enterprise-assigned unique ID.
language The language in which the conversation happened with the bot.
timestamp The response date is converted into timestamp format.
pinned Indicates whether the message is pinned – true or false.
channel Name of the channel through which the conversation occurred.
winningIntent An array containing the winning intent(s) for the utterance.
isAmbiguous Indicates whether the intent is ambiguous – true or false.
ambiguousIntents An array of ambiguous intents, if applicable.
taskName The name of the task associated with the conversation.
nodeName The node name. This parameter is retrieved only for the Performance metric.
type The type of the node. This parameter is retrieved only for the Performance metric.
status The status of the task. This parameter is retrieved only for the Performance metric.
statusCode The status code of the task. This parameter is retrieved only for the Performance metric.
responseTime The response time for the task. This parameter is retrieved only for the Performance metric.
flow An array of task flows.
taskId The unique identifier for the task.
koralogstatusId The unique identifier for the koralog status.
customTags Custom tags added to the user’s profile.
customTags.userTags User tags added to the user’s profile information.
userTags.name Tag’s name.
userTags.value Tag’s value.
customTags.sessionTags Custom tags added to the conversation session.
customTags.messagesTags Meta tags to filter the conversations.
NLAnalysis Contains natural language analysis results, including intent recognition and other natural language processing details.

The ‘NLAnalysis’ object includes multiple sub-objects such as ‘intentRescoring’, ‘nlProcessing’, ‘ml’ (machine learning analysis), ‘fm’ (fundamental meaning analysis), ‘faq’ (frequently asked questions analysis), and finalResolver. Each of these sub-objects contains information related to the analysis process, such as linguistic analysis, intent recognition, and the elimination of unlikely intents, etc.

NLAnalysis.debugTitle The metric type in the NL Analysis. Possible values are:

  • Intent Match Successful
  • Intent Match Failed
  • Intent Failed/Abandoned
  • Intent Completed Successfully
  • Unhandled Utterances
  • Performance
NLAnalysis.result The result of the NL analysis. For example, the result can be an unhandled utterance or a failed task.
NLAnalysis.messageStoreId A unique identifier for the message stored in the system.
NLAnalysis.channelId The identifier for the channel where the conversation took place.
NLAnalysis.bot The name of the bot that handled the conversation.
NLAnalysis.botid The unique identifier for the bot.
NLAnalysis.skipConversation If set to true, skips the conversation record. If false, do not skip the conversation.
NLAnalysis.task The name of the task associated with the conversation.
NLAnalysis.botLanguage The language used by the bot.
NLAnalysis.nluLanguage The language in which the NLP training happened for that particular bot language.
NLAnalysis.taskId The unique identifier for the task associated with the conversation.
NLAnalysis.isDeveloper Whether the session was initiated by a developer –  true or false.
NLAnalysis.reason The NL analysis reason object.              
NLAnalysis.reason.cause The cause for NL analysis failure. For example, the script node failure.
NLAnalysis.reason.causeId The NL analysis cause id.
NLAnalysis.fields The fields; Contains additional fields associated with the interaction.
NLAnalysis.logSequenceId The unique log sequence identifier.
NLAnalysis.intentStatus The status of the intent.
NLAnalysis.subType The task subtype.  For example, a dialog.
NLAnalysis.channelInfo The bot channel information.
NLAnalysis.input An array containing the user’s input.
NLAnalysis.taskContextId The unique task context identifier.
NLAnalysis.intentRescoring Indicates whether intent rescoring was enabled – true or false. (true means the system may reevaluate and rescore intents during the processing of the user’s input.)
NLAnalysis.isPreferDefinitiveMatch Indicates whether the system prefers a definitive match when recognizing intents – true or false.
NLAnalysis.scoringModel The scoring model used for intent recognition. Possible value – original.
NLAnalysis.toneAnalysis The toneAnalysis object; Contains the tone analysis of the task. Learn more.
NLAnalysis.nlProcessing The nlProcessing object; Contains information about the linguistic analysis and natural language processing of the user’s input.
NLAnalysis.nlProcessing.originalInput The original user input.
NLAnalysis.nlProcessing.spellCorrectedInput If spelling correction is applied, it would contain the corrected user input. (Null indicates no spelling correction applied.)
NLAnalysis.nlProcessing.canonical The canonical representation of the input; typically represents a normalized or recognized form of the user’s input.
NLAnalysis.nlProcessing.wordAnalysis An array of objects, each containing a detailed analysis of individual words in the user’s input.
NLAnalysis.nlProcessing.wordAnalysis.index The position of the word in the input.
NLAnalysis.nlProcessing.wordAnalysis.word The recognized/analyzed word.
NLAnalysis.nlProcessing.wordAnalysis.ignored Indicates whether the word was ignored in the analysis – true or false.
NLAnalysis.nlProcessing.wordAnalysis.pos Part-of-speech tagging for the word.
NLAnalysis.nlProcessing.wordAnalysis.role The role or function of the word in the context.
NLAnalysis.nlProcessing.wordAnalysis.original The original word.
NLAnalysis.nlProcessing.wordAnalysis.processedWord The processed word.
NLAnalysis.ml The ml object; Contains information related to machine learning analysis, including intent recognition and elimination of unlikely intents. (Most of the parameters/values returned by the object are used internally.)
NLAnalysis.fm The fm object; Contains information related to fundamental meaning analysis, provides insights into the scoring, matching, and elimination of tasks, etc. (Most of the parameters/values returned by the object are used internally.)   
NLAnalysis.faq The faq object; Contains detailed information about the analysis of user input related to faq. (Most of the parameters/values returned by the object are used internally.)  
NLAnalysis.finalResolver The finalResolver object; Contains information related to the final resolution process and the determination of the response or action to be taken based on the user’s input. (Most of the parameters/values returned by the object are used internally.)
totalCount The total number of records identified as per the API request parameters.

Get Analytics API

The Get Analytics API allows you to retrieve metrics data related to intent detection and task performance. The API provides information about various metrics, including Intents Found, Intents not Found, Unhandled Utterances, Failed Tasks, Successful Tasks, and Performance Logs.

Method POST
Endpoint https://{{host}}/api/public/bot/{{BotID}}/getAnalytics
Content Type application/json
Authorization auth: {{JWT}}

See How to generate the JWT Token.

API Scope
  • Bot Builder: Metrics
  • Admin Console: Not Applicable

Path Parameters

Parameter Required/Optional Description
host Required Environment URL, for example, https://bots.kore.ai
BotID Required Bot ID or Stream ID. You can access it from the General Settings page of the bot.

Sample Request

The following sample request shows how to retrieve unhandled utterance analytics data with specific filters. You can modify the type and filters parameters to retrieve different types of analytics data as needed.

curl --location --request POST 'https://bots.kore.ai/api/public/bot/st-xxxxxxd-xxxx-xxxx-xxxx-xxxxxxxxxx/getAnalytics' \
--header 'auth: {{YOUR_JWT_ACCESS_TOKEN}}' \
--header 'content-type: application/json' \
--data-raw '{
    "type": "unhandledutterance",
    "filters": {
        "from": "2022-09-11T17:25:09.698Z",
        "to": "2022-09-25T17:25:09.698Z",
       
           
        "channel": [
            "rtm"
        ],
        "isAmbiguous": false,
        "isDeveloper": false,
        "trained": false,
        "userId": [
            "u-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxx"
        ]
       
       
    },
    "sort":
        { "order": "asc",
          "by": "nodeName" },
   
    "limit": 50
}'

Request Body Parameters

Parameter Type Description
type string, required Indicates the type of metrics for which you can retrieve data:

  • successintent
  • failintent
  • successtask
  • failtask
  • performance
  • unhandledutterance
filters object, required A set of filters to narrow down the analytics data.
filters.from string, required The start timestamp for the data retrieval.
filters.to string, required The end timestamp for the data retrieval.
filters.channel array of strings, optional An array containing channel names to filter data by; the default channel is “rtm”.

Accepted channels are:

  • “skypeforbusiness”
  • “msteams”
  • “twitter”
  • “spark”
  • “rtm”
  • “facebook”
  • “slack”
  • “skype”
  • “kore”
  • “email”
  • “sms”
  • “facebook”
  • “ringcentral”
  • “jabber”
  • “yammer”
  • “alexa”
  • “twiliovoice”
  • “telegram”
  • “ivr”
  • “ivrVoice”
  • “smartassist”
  • “line”
  • “liveperson”
  • “googleactions”
  • “hangoutchat”
  • “mattermost”
  • “rcs”
filters.channel.channelUIds array of strings, optional The end-user’s identity provided by the channel.

Note: For “ivr” channel, it’s a combination of {accountId}/{channel}/{channelUId}.
For example,
"channelUIds": ["5fb6a04e20ab9d2c19cb73xx/ivrinst-893b4d4f-1fc1-54c3-b3xx-fa7200c4c2xx/first.last@domain.com"]

filters.isAmbiguous boolean, optional Whether to include ambiguous intents or not – set to true or false.
filters.isDeveloper boolean, optional Whether to include developer metrics – set to true or false.
filters.trained boolean, optional Whether to include trained intents or not – set to true or false.
filter.taskId array of strings, optional To filter based on the task IDs.
filters.userId array of strings, optional To filter based on user IDs.
filters.tags object, optional Meta tags to filter the records.
Usage example:

"tags": {
         "and": [
                 {
                  "name": "user",
                  "values": ["uservalue"],
                  "type": "user"
                  },
                  {
                   "name": "message",
                   "values": ["mvalue"],
                   "type": "message"
                   }
                ]
           }
sort object, optional An object containing the sorting criteria to apply to the data being retrieved:

  • order (string, required): Sorting order, either “asc” for ascending or “desc” for descending.
  • by (string, required): The field/column by which the data should be sorted.

Usage example:

"sort": 
       { "order": "<desc/asc>", 
          "by": "<column name>" }
limit integer, required Indicates the number of records to be returned in the result set.
skip integer, required The number of records to be skipped from the result set.

Sample Response

{
    "moreAvailable": false,
    "result": [
        {
            "_id": "63xxxxxxxxxxxxxxxxx",
            "messageId": "ms-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxx",
            "sessionId": "63xxxxxxxxxxxxxxx",
            "utterance": "aslfkj",
            "intent": "Mobile Enquiry",
            "userId": "u-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxx",
            "channelUId": "test@abc.xyz",
            "language": "en",
            "timestamp": "2022-09-24T08:24:39.840Z",
            "pinned": false,
            "channel": "rtm",
            "winningIntent": [],
            "isAmbiguous": false,
            "ambiguousIntents": [],
            "taskName": "Mobile Enquiry",
            "flow": [],
            "taskId": "dg-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx",
            "koralogstatusId": "f-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxx-xxxxxxxxxxx",
            "customTags": {
                "userTags": [
                    {
                        "name": "Name",
                        "value": "John"
                    }
                ],
                "sessionTags": [],
                "messageTags": []
            },
            "NLAnalysis": {
                "result": "unhandledUtterance",
                "messageStoreId": "ms-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxx",
                "channelId": "st-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxx:u-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxx:rtm",
                "bot": "Channel Check",
                "botid": "st-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxx",
                "skipConversation": true,
                "task": "Mobile Enquiry",
                "botLanguage": "en-US",
                "nluLanguage": "en-US",
                "taskId": "dg-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxx",
                "fields": {},
                "logSequenceId": "f-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxx-xxxxxxxxxx",
                "intentStatus": "published",
                "subType": "dialog",
                "channelInfo": "st-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx:u-xxxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx:rtm",
                "input": [
                    "aslfkj"
                ],
                "taskContextId": "dcx-xxxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx",
                "NLAnalysis": {
                    "intentRescoring": true,
                    "isPreferDefinitiveMatch": true,
                    "scoringModel": "original",
                    "toneAnalysis": {},
                    "nlProcessing": {
                        "originalInput": "aslfkj",
                        "spellCorrectedInput": null,
                        "canonical": "Aslak",
                        "wordAnalysis": [
                            {
                                "index": 1,
                                "word": "Aslak",
                                "ignored": false,
                                "pos": "Noun_proper_singular ",
                                "role": "MAINSUBJECT ",
                                "original": "aslfkj",
                                "processedWord": "Aslak"
                            }
                        ]
                    },
                    "ml": {
                        "intentModel": "bot level intent model",
                        "eliminated": [
                            {
                                "task": "Book Appointment",
                                "state": "published",
                                "score": 0.017055602351504544,
                                "scoringCriteria": "Probabilistic score",
                                "matchType": "unlikely"
                            },
                            {
                                "task": "Transfer Money",
                                "state": "published",
                                "score": 0.011911144983740555,
                                "scoringCriteria": "Probabilistic score",
                                "matchType": "unlikely"
                            },
                            {
                                "task": "Show Balance",
                                "state": "published",
                                "score": 0.009209086809082547,
                                "scoringCriteria": "Probabilistic score",
                                "matchType": "unlikely"
                            }
                        ],
                        "namedEntityRecognition": []
                    },
                    "faq": {
                        "demystify": {
                            "lemmatizer_used": "PATTERN",
                            "normalizedQuery": "aslfkj",
                            "OntologyTraits": [],
                            "failed_questions": {},
                            "SelectedPathCount": 3,
                            "ExtractedEntities": [],
                            "ContextEntities": [],
                            "PreConditionNodes": [],
                            "filtered_questions": {
                                "score": [],
                                "traits": []
                            }
                        }
                    }
                },
                "language": "en",
                "channel": "rtm",
                "userId": "u-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx",
                "time": "2022-09-24T08:24:39.808Z",
                "channelclient": "botbuilder",
                "_id": "f-121d2486-xxxx-xxxx-xxxx-xxxxxxxxxx-xxxxxxxxxx",
                "resourceid": "korastatuslogs",
                "entityOrgId": "o-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxx",
                "iv": "VP47awbZ8JRCoqFtgPx7fA==",
                "cek": {
                    "header": {
                        "alg": "dir",
                        "enc": "aes-256-cbc",
                        "kid": "k-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxx"
                    }
                },
                "ire": true
            },
            "nodeName": "Entity_color",
            "promptType": "entity"
        },
        {
            "_id": "63xxxxxxxxxxxx",
            "messageId": "ms-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxx",
            "sessionId": "63xxxxxxxxxxxxxxxxx",
            "utterance": "alskd",
            "intent": "Mobile Enquiry",
            "userId": "u-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxx",
            "channelUId": "ramakrishnakoretest@getnada.com",
            "language": "en",
            "timestamp": "2022-09-24T08:24:50.257Z",
            "pinned": false,
            "channel": "rtm",
            "winningIntent": [],
            "isAmbiguous": false,
            "ambiguousIntents": [],
            "taskName": "Mobile Enquiry",
            "flow": [],
            "taskId": "dg-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx",
            "koralogstatusId": "f-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx-xxxxxxx",
            "customTags": {
                "userTags": [
                    {
                        "name": "Name",
                        "value": "Krishna"
                    }
                ],
                "sessionTags": [],
                "messageTags": []
            },
            "NLAnalysis": {
                "result": "unhandledUtterance",
                "messageStoreId": "ms-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxx",
                "channelId": "st-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxx:u-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx:rtm",
                "bot": "Channel Check",
                "botid": "st-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx",
                "skipConversation": true,
                "task": "Mobile Enquiry",
                "botLanguage": "en-US",
                "nluLanguage": "en-US",
                "taskId": "dg-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx",
                "fields": {},
                "logSequenceId": "f-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx-xxxxxxx",
                "intentStatus": "published",
                "subType": "dialog",
                "channelInfo": "st-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxx:u-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx:rtm",
                "input": [
                    "alskd"
                ],
                "taskContextId": "dcx-b3e58798-ed3b-5f3d-9894-2e26758001eb",
                "NLAnalysis": {
                    "intentRescoring": true,
                    "isPreferDefinitiveMatch": true,
                    "scoringModel": "original",
                    "toneAnalysis": {},
                    "nlProcessing": {
                        "originalInput": "alskd",
                        "spellCorrectedInput": null,
                        "canonical": "alskd",
                        "wordAnalysis": [
                            {
                                "index": 1,
                                "word": "unknown-word",
                                "ignored": false,
                                "pos": "Noun_infinitive Noun_singular Verb_infinitive Verb_present Adjective_normal Adverb ",
                                "original": "alskd",
                                "processedWord": "alskd"
                            }
                        ]
                    },
                    "ml": {
                        "intentModel": "bot level intent model",
                        "eliminated": [
                            {
                                "task": "Book Appointment",
                                "state": "published",
                                "score": 0.017055602351504544,
                                "scoringCriteria": "Probabilistic score",
                                "matchType": "unlikely"
                            },
                            {
                                "task": "Transfer Money",
                                "state": "published",
                                "score": 0.011911144983740555,
                                "scoringCriteria": "Probabilistic score",
                                "matchType": "unlikely"
                            },
                            {
                                "task": "Show Balance",
                                "state": "published",
                                "score": 0.009209086809082547,
                                "scoringCriteria": "Probabilistic score",
                                "matchType": "unlikely"
                            }
                        ],
                        "namedEntityRecognition": []
                    },
                    "faq": {
                        "demystify": {
                            "lemmatizer_used": "PATTERN",
                            "normalizedQuery": "alskd",
                            "OntologyTraits": [],
                            "failed_questions": {},
                            "SelectedPathCount": 3,
                            "ExtractedEntities": [],
                            "ContextEntities": [],
                            "PreConditionNodes": [],
                            "filtered_questions": {
                                "score": [],
                                "traits": []
                            }
                        }
                    }
                },
                "language": "en",
                "channel": "rtm",
                "userId": "u-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxx",
                "time": "2022-09-24T08:24:50.226Z",
                "channelclient": "botbuilder",
                "_id": "f-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxx-xxxxxxxx",
                "resourceid": "korastatuslogs",
                "entityOrgId": "o-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxx",
                "iv": "+Kl5i6AAFJp0g3NkExn+Og==",
                "cek": {
                    "header": {
                        "alg": "dir",
                        "enc": "aes-256-cbc",
                        "kid": "k-xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx"
                    }
                },
                "ire": true
            },
            "nodeName": "Entity_capacity",
            "promptType": "entity"
        }
    ],
    "totalCount": 2
}

Response Body Parameters

PARAMETER DESCRIPTION
moreAvailable Indicates if the API has returned all the records or if more are available, based on the pagination criteria.

True if more records are available. False if there are no more records to be retrieved.

result Contains complete information about the metrics.
id The unique identifier for the record.
messagesId The unique identifier for the message record.
sessionId The unique identifier for the session.
utterance The user utterance/input.
intent The identified intent for the user’s utterance/input.
userId The unique identifier for the user.
channelUId The end-user’s identity provided by the channel. It can be the user’s email ID or enterprise-assigned unique ID.
language The language in which the conversation happened with the bot.
timestamp The response date is converted into timestamp format.
pinned Indicates whether the message is pinned – true or false.
channel Name of the channel through which the conversation occurred.
winningIntent An array containing the winning intent(s) for the utterance.
isAmbiguous Indicates whether the intent is ambiguous – true or false.
ambiguousIntents An array of ambiguous intents, if applicable.
taskName The name of the task associated with the conversation.
nodeName The node name. This parameter is retrieved only for the Performance metric.
type The type of the node. This parameter is retrieved only for the Performance metric.
status The status of the task. This parameter is retrieved only for the Performance metric.
statusCode The status code of the task. This parameter is retrieved only for the Performance metric.
responseTime The response time for the task. This parameter is retrieved only for the Performance metric.
flow An array of task flows.
taskId The unique identifier for the task.
koralogstatusId The unique identifier for the koralog status.
customTags Custom tags added to the user’s profile.
customTags.userTags User tags added to the user’s profile information.
userTags.name Tag’s name.
userTags.value Tag’s value.
customTags.sessionTags Custom tags added to the conversation session.
customTags.messagesTags Meta tags to filter the conversations.
NLAnalysis Contains natural language analysis results, including intent recognition and other natural language processing details.

The ‘NLAnalysis’ object includes multiple sub-objects such as ‘intentRescoring’, ‘nlProcessing’, ‘ml’ (machine learning analysis), ‘fm’ (fundamental meaning analysis), ‘faq’ (frequently asked questions analysis), and finalResolver. Each of these sub-objects contains information related to the analysis process, such as linguistic analysis, intent recognition, and the elimination of unlikely intents, etc.

NLAnalysis.debugTitle The metric type in the NL Analysis. Possible values are:

  • Intent Match Successful
  • Intent Match Failed
  • Intent Failed/Abandoned
  • Intent Completed Successfully
  • Unhandled Utterances
  • Performance
NLAnalysis.result The result of the NL analysis. For example, the result can be an unhandled utterance or a failed task.
NLAnalysis.messageStoreId A unique identifier for the message stored in the system.
NLAnalysis.channelId The identifier for the channel where the conversation took place.
NLAnalysis.bot The name of the bot that handled the conversation.
NLAnalysis.botid The unique identifier for the bot.
NLAnalysis.skipConversation If set to true, skips the conversation record. If false, do not skip the conversation.
NLAnalysis.task The name of the task associated with the conversation.
NLAnalysis.botLanguage The language used by the bot.
NLAnalysis.nluLanguage The language in which the NLP training happened for that particular bot language.
NLAnalysis.taskId The unique identifier for the task associated with the conversation.
NLAnalysis.isDeveloper Whether the session was initiated by a developer –  true or false.
NLAnalysis.reason The NL analysis reason object.              
NLAnalysis.reason.cause The cause for NL analysis failure. For example, the script node failure.
NLAnalysis.reason.causeId The NL analysis cause id.
NLAnalysis.fields The fields; Contains additional fields associated with the interaction.
NLAnalysis.logSequenceId The unique log sequence identifier.
NLAnalysis.intentStatus The status of the intent.
NLAnalysis.subType The task subtype.  For example, a dialog.
NLAnalysis.channelInfo The bot channel information.
NLAnalysis.input An array containing the user’s input.
NLAnalysis.taskContextId The unique task context identifier.
NLAnalysis.intentRescoring Indicates whether intent rescoring was enabled – true or false. (true means the system may reevaluate and rescore intents during the processing of the user’s input.)
NLAnalysis.isPreferDefinitiveMatch Indicates whether the system prefers a definitive match when recognizing intents – true or false.
NLAnalysis.scoringModel The scoring model used for intent recognition. Possible value – original.
NLAnalysis.toneAnalysis The toneAnalysis object; Contains the tone analysis of the task. Learn more.
NLAnalysis.nlProcessing The nlProcessing object; Contains information about the linguistic analysis and natural language processing of the user’s input.
NLAnalysis.nlProcessing.originalInput The original user input.
NLAnalysis.nlProcessing.spellCorrectedInput If spelling correction is applied, it would contain the corrected user input. (Null indicates no spelling correction applied.)
NLAnalysis.nlProcessing.canonical The canonical representation of the input; typically represents a normalized or recognized form of the user’s input.
NLAnalysis.nlProcessing.wordAnalysis An array of objects, each containing a detailed analysis of individual words in the user’s input.
NLAnalysis.nlProcessing.wordAnalysis.index The position of the word in the input.
NLAnalysis.nlProcessing.wordAnalysis.word The recognized/analyzed word.
NLAnalysis.nlProcessing.wordAnalysis.ignored Indicates whether the word was ignored in the analysis – true or false.
NLAnalysis.nlProcessing.wordAnalysis.pos Part-of-speech tagging for the word.
NLAnalysis.nlProcessing.wordAnalysis.role The role or function of the word in the context.
NLAnalysis.nlProcessing.wordAnalysis.original The original word.
NLAnalysis.nlProcessing.wordAnalysis.processedWord The processed word.
NLAnalysis.ml The ml object; Contains information related to machine learning analysis, including intent recognition and elimination of unlikely intents. (Most of the parameters/values returned by the object are used internally.)
NLAnalysis.fm The fm object; Contains information related to fundamental meaning analysis, provides insights into the scoring, matching, and elimination of tasks, etc. (Most of the parameters/values returned by the object are used internally.)   
NLAnalysis.faq The faq object; Contains detailed information about the analysis of user input related to faq. (Most of the parameters/values returned by the object are used internally.)  
NLAnalysis.finalResolver The finalResolver object; Contains information related to the final resolution process and the determination of the response or action to be taken based on the user’s input. (Most of the parameters/values returned by the object are used internally.)
totalCount The total number of records identified as per the API request parameters.
Menu