Integrate language operator results with your application

To build an end-to-end solution with Conversation Intelligence, integrate language operator results with your application. You can do this in either of the following ways:

Rule Execution webhook: Receives language operator results as they're generated. Use for real-time activation.
Intelligence API: Retrieves historical language operator results and conversations processed by Intelligence. Use for post-conversation activation.

Rule Execution webhook

The Rule Execution webhook sends language operator results to your webhook endpoint as an HTTP POST request when they're generated. Use these results to inform your application's next steps, such as:

Update agent UIs
Trigger alerts or notifications
Invoke downstream automation

To receive this webhook, you must define a rule with a valid action (type: webhook) in your intelligence configuration.

Webhook payload

The webhook payload includes:

A list of all language operator results generated by the rule execution
Execution details, including:
- The trigger that fired the rule
- The resolved context (Conversation Memory and Enterprise Knowledge) used during execution
- Communications range and participant information
Execution metadata, including latency, model used, and input/output character counts
Intelligence configuration and conversation identifiers

For more information about the webhook payload structure and properties, see Rule Execution webhook.

Example: Rule Execution webhook payload

1{
2  "accountId": "ACxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
3  "conversationId": "conv_conversation_772a49ae-48e7-4d18-9db5-a40f6203de01",
4  "intelligenceConfiguration": {
5    "id": "intelligence_configuration_0hcq1h4zbqcpr8ceyyk4cde7kr",
6    "displayName": "Real-time Sentiment Analyzer",
7    "version": 1,
8    "ruleId": "intelligence_configurationrule_01kc6nrdc4f509sgccvd8hc27c"
9  },
10  "operatorResults": [
11    {
12      "id": "intelligence_operatorresult_01kc6nrdc4f9vrt6t2ypcy8b75",
13      "operator": {
14        "id": "intelligence_operator_01kcrvw16kfa88qvgrfmr7y151",
15        "displayName": "Sentiment",
16        "version": 2,
17        "parameters": null
18      },
19      "outputFormat": "CLASSIFICATION",
20      "result": {
21        "label": "positive"
22      },
23      "dateCreated": "2026-03-11T12:33:36.143498Z",
24      "referenceIds": [],
25      "executionDetails": {
26        "trigger": {
27          "on": "COMMUNICATION",
28          "timestamp": "2026-03-11T12:33:35.987654Z"
29        },
30        "communications": {
31          "first": "conv_communication_00000000000000000000000000",
32          "last": "conv_communication_00000000000000000000000001"
33        },
34        "channels": [
35          "SMS"
36        ],
37        "participants": [
38          {
39            "id": "conv_participant_00000000000000000000000000",
40            "profileId": "mem_profile_00000000000000000000000000",
41            "type": "CUSTOMER"
42          },
43          {
44            "id": "conv_participant_00000000000000000000000001",
45            "profileId": null,
46            "type": "HUMAN_AGENT"
47          }
48        ],
49        "resolvedContext": {
50          "memory": {
51            "profileId": "mem_profile_00000000000000000000000000",
52            "memoryStoreId": "mem_store_00000000000000000000000000"
53          },
54          "knowledge": {
55            "sources": [
56              {
57                "baseId": "know_knowledgebase_00000000000000000000000000",
58                "sourceId": "know_knowledge_00000000000000000000000000"
59              }
60            ]
61          }
62        }
63      },
64      "metadata": {
65        "system": {
66          "latencyMs": 1842,
67          "resolvedModel": "gpt-5.4-mini",
68          "inputCharacters": 3830,
69          "outputCharacters": 150,
70          "inputTruncated": false
71        }
72      }
73    }
74  ]
75}

Conversation Intelligence API

Use the OperatorResults and Conversations resources to retrieve historical language operator results and conversations processed by your intelligence configuration. You can use this data to:

Analyze post-conversation results
Report and audit
Recover if a webhook delivery is missed

OperatorResults resource

The OperatorResults resource returns:

The result of the language operator
Rule execution metadata, including:
- Parameter values
- Context used
- Rule and intelligence configuration IDs

You can filter results by:

Intelligence configuration
Conversation

The following is an example request and response using the OperatorResults resource:

Retrieve a list of language operator results

1// Download the helper library from https://www.twilio.com/docs/node/install
2const twilio = require("twilio"); // Or, for ESM: import twilio from "twilio";
3
4// Find your Account SID at twilio.com/console
5// Provision API Keys at twilio.com/console/runtime/api-keys
6// and set the environment variables. See http://twil.io/secure
7// For local testing, you can use your Account SID and Auth token
8const accountSid = process.env.TWILIO_ACCOUNT_SID;
9const apiKey = process.env.TWILIO_API_KEY;
10const apiSecret = process.env.TWILIO_API_SECRET;
11const client = twilio(apiKey, apiSecret, { accountSid: accountSid });
12
13async function listOperatorResults() {
14  const operatorResults = await client.intelligence.v3.operatorResults.list({
15    limit: 20,
16  });
17
18  operatorResults.forEach((o) => console.log(o.outputFormat));
19}
20
21listOperatorResults();

Response

1{
2  "items": [
3    {
4      "id": "intelligence_operatorresult_01k6fc25s7epm9qtk8rszbv3q5",
5      "accountId": "AC00000000000000000000000000000000",
6      "outputFormat": "JSON",
7      "intelligenceConfiguration": {
8        "id": "intelligence_configuration_01kermhm82e5mr98nbeh1hpmbn",
9        "ruleId": "intelligence_configurationrule_01kermhm81fwfvy7j0f7h7v5mr",
10        "version": 1
11      },
12      "conversationId": "conv_conversation_01k1etk2y5f1y9fpe2epfdtvv2",
13      "operator": {
14        "id": "intelligence_operator_01kcgy1ew0e9x8re6jq542zt8b",
15        "version": 1,
16        "parameters": {
17          "scale": 5
18        }
19      },
20      "dateCreated": "2026-01-15T10:45:30Z",
21      "referenceIds": [
22        "conv_communication_01k1etk2y5f1y9fpe2epfdtvv2"
23      ],
24      "executionDetails": {
25        "trigger": {
26          "on": "CONVERSATION_END",
27          "timestamp": "2026-01-15T10:45:25Z"
28        },
29        "communications": {
30          "first": "conv_communication_01k1etk2y5f1y9fpe2epfdtvv2",
31          "last": "conv_communication_01k1etk2y5f1y9fpe2epfdtvv9"
32        },
33        "channels": [
34          "VOICE"
35        ],
36        "participants": [
37          {
38            "id": "conv_participant_01k1etx3jbfx88476ccja0889c",
39            "profileId": "mem_profile_01k6fbz0v4f4e9qtk8p8z7y3w1",
40            "type": "CUSTOMER"
41          },
42          {
43            "id": "conv_participant_01k1etx3jbfx88476ccja0889d",
44            "type": "HUMAN_AGENT"
45          }
46        ],
47        "resolvedContext": {
48          "memory": {
49            "profileId": "mem_profile_00000000000000000000000000",
50            "memoryStoreId": "mem_store_00000000000000000000000000"
51          },
52          "knowledge": {
53            "sources": [
54              {
55                "baseId": "know_knowledgebase_00000000000000000000000000",
56                "sourceId": "know_knowledge_00000000000000000000000000"
57              }
58            ]
59          }
60        }
61      },
62      "result": {
63        "score": 5,
64        "explanation": "The agent followed the script closely and addressed all key points effectively."
65      }
66    },
67    {
68      "id": "intelligence_operatorresult_01k6fc25s7epm9qtk8rszbv3q6",
69      "accountId": "AC00000000000000000000000000000000",
70      "outputFormat": "CLASSIFICATION",
71      "intelligenceConfiguration": {
72        "id": "intelligence_configuration_01kermhm82e5mr98nbeh1hpmbn",
73        "ruleId": "intelligence_configurationrule_01kermhm81fwfvy7j0f7h7v5mr",
74        "version": 1
75      },
76      "conversationId": "conv_conversation_01k1etk2y5f1y9fpe2epfdtvv2",
77      "operator": {
78        "id": "intelligence_operator_01kcgy1ew0e9x8re6jq542zt9c",
79        "version": 2,
80        "parameters": {}
81      },
82      "dateCreated": "2026-01-15T10:45:35Z",
83      "referenceIds": [
84        "conv_communication_01k1etk2y5f1y9fpe2epfdtvv2"
85      ],
86      "executionDetails": {
87        "trigger": {
88          "on": "CONVERSATION_END",
89          "timestamp": "2026-01-15T10:45:25Z"
90        },
91        "communications": {
92          "first": "conv_communication_01k1etk2y5f1y9fpe2epfdtvv2",
93          "last": "conv_communication_01k1etk2y5f1y9fpe2epfdtvv9"
94        },
95        "channels": [
96          "VOICE"
97        ],
98        "participants": [
99          {
100            "id": "conv_participant_01k1etx3jbfx88476ccja0889c",
101            "type": "CUSTOMER"
102          },
103          {
104            "id": "conv_participant_01k1etx3jbfx88476ccja0889d",
105            "type": "HUMAN_AGENT"
106          }
107        ]
108      },
109      "result": {
110        "label": "POSITIVE"
111      }
112    }
113  ],
114  "meta": {
115    "key": "items",
116    "pageSize": 2,
117    "nextToken": "next_page_token_example"
118  }
119}

Conversations resource

The Conversations resource returns Conversations processed by Conversation Intelligence and includes:

Conversation metadata
Intelligence configuration details
Language operators and rules that ran on the Conversation

You can filter Conversations by:

Intelligence configuration
Language operators that have been executed
Conversation metadata, such as channel, participant information, and date range

The following is an example request and response using the Conversations resource:

Retrieve a list of Conversations processed by Conversation Intelligence

1// Download the helper library from https://www.twilio.com/docs/node/install
2const twilio = require("twilio"); // Or, for ESM: import twilio from "twilio";
3
4// Find your Account SID at twilio.com/console
5// Provision API Keys at twilio.com/console/runtime/api-keys
6// and set the environment variables. See http://twil.io/secure
7// For local testing, you can use your Account SID and Auth token
8const accountSid = process.env.TWILIO_ACCOUNT_SID;
9const apiKey = process.env.TWILIO_API_KEY;
10const apiSecret = process.env.TWILIO_API_SECRET;
11const client = twilio(apiKey, apiSecret, { accountSid: accountSid });
12
13async function listConversations() {
14  const conversations = await client.intelligence.v3.conversations.list({
15    limit: 20,
16  });
17
18  conversations.forEach((c) => console.log(c.id));
19}
20
21listConversations();

Response

1{
2  "items": [
3    {
4      "id": "conv_conversation_01k1etk2y5f1y9fpe2epfdtvv2",
5      "accountId": "AC00000000000000000000000000000000",
6      "name": "Customer Support Call - Order #12345",
7      "status": "CLOSED",
8      "createdAt": "2026-01-15T10:30:00Z",
9      "updatedAt": "2026-01-15T10:45:30Z",
10      "intelligenceConfigurationIds": [
11        "intelligence_configuration_01kermhm82e5mr98nbeh1hpmbn"
12      ],
13      "conversationConfigurationId": "conv_configuration_00000000000000000000000000",
14      "channels": [
15        "VOICE"
16      ],
17      "channelIds": [
18        "CA1234567890abcdef1234567890abcdef"
19      ],
20      "participants": [
21        {
22          "id": "conv_participant_01k1etx3jbfx88476ccja0889c",
23          "name": "John Customer",
24          "type": "CUSTOMER",
25          "addressValues": [
26            "+15551234567"
27          ]
28        },
29        {
30          "id": "conv_participant_01k1etx3jbfx88476ccja0889d",
31          "name": "Sarah Agent",
32          "type": "HUMAN_AGENT",
33          "addressValues": [
34            "agent-sarah@example.com"
35          ]
36        }
37      ],
38      "operatorResultIds": [
39        "intelligence_operatorresult_01k6fc25s7epm9qtk8rszbv3q5"
40      ]
41    },
42    {
43      "id": "conv_conversation_01k1etk2y5f1y9fpe2epfdtvv3",
44      "accountId": "AC00000000000000000000000000000000",
45      "name": "Sales Inquiry - WhatsApp",
46      "status": "ACTIVE",
47      "createdAt": "2026-01-15T14:20:00Z",
48      "updatedAt": "2026-01-15T14:22:00Z",
49      "intelligenceConfigurationIds": [
50        "intelligence_configuration_01kermhm82e5mr98nbeh1hpmbn"
51      ],
52      "conversationConfigurationId": "conv_configuration_00000000000000000000000000",
53      "channels": [
54        "WHATSAPP"
55      ],
56      "channelIds": [
57        "SM9876543210fedcba9876543210fedcba"
58      ],
59      "participants": [
60        {
61          "id": "conv_participant_01k1etx3jbfx88476ccja0889e",
62          "name": "Maria Customer",
63          "type": "CUSTOMER",
64          "addressValues": [
65            "whatsapp:+15559876543"
66          ]
67        },
68        {
69          "id": "conv_participant_01k1etx3jbfx88476ccja0889f",
70          "name": "AI Sales Assistant",
71          "type": "AI_AGENT",
72          "addressValues": [
73            "bot-sales@example.com"
74          ]
75        }
76      ],
77      "operatorResultIds": [
78        "intelligence_operatorresult_01k6fc25s7epm9qtk8rszbv3q7"
79      ]
80    }
81  ],
82  "meta": {
83    "key": "items",
84    "pageSize": 2,
85    "nextToken": "next_page_token_example"
86  }
87}

Next steps

View language operator results in Twilio Console.