This workflow follows the Execute Workflow Trigger → HTTP Request recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"meta": {
"templateCredsSetupCompleted": true
},
"nodes": [
{
"id": "e893e48c-1b69-413a-90d7-ad6ce5987e7c",
"name": "Execute Workflow Trigger",
"type": "n8n-nodes-base.executeWorkflowTrigger",
"position": [
-180,
-60
],
"parameters": {},
"typeVersion": 1
},
{
"id": "1c42e95b-705d-43ae-91ce-1029334b9e9a",
"name": "Retrieve detailed call data",
"type": "n8n-nodes-base.httpRequest",
"position": [
60,
40
],
"parameters": {
"url": "https://api.gong.io/v2/calls/extensive",
"options": {
"fullResponse": true
},
"requestMethod": "POST",
"authentication": "genericCredentialType",
"jsonParameters": true,
"genericAuthType": "httpHeaderAuth",
"bodyParametersJson": "={\n \"contentSelector\": {\n \"context\": \"Extended\",\n \"contextTiming\": [\"Now\", \"TimeOfCall\"],\n \"exposedFields\": {\n \"collaboration\": {\n \"publicComments\": true\n },\n \"content\": {\n \"pointsOfInterest\": true,\n \"structure\": true,\n \"topics\": true,\n \"trackers\": true\n },\n \"interaction\": {\n \"personInteractionStats\": true,\n \"questions\": true,\n \"speakers\": true,\n \"video\": true\n },\n \"media\": false,\n \"parties\": true\n }\n },\n \"filter\": {\n \"callIds\": [\"{{ $json['calldata[0].calls'].id }}\"]\n }\n}"
},
"credentials": {
"httpHeaderAuth": {
"name": "<your credential>"
}
},
"typeVersion": 2
},
{
"id": "69c9ef1a-9ef4-4c3f-ab62-a5c9b2a10a4e",
"name": "Get transcript",
"type": "n8n-nodes-base.httpRequest",
"position": [
60,
-140
],
"parameters": {
"url": "https://api.gong.io/v2/calls/transcript?callIds=1807130744801961509",
"options": {
"fullResponse": true
},
"requestMethod": "POST",
"authentication": "genericCredentialType",
"jsonParameters": true,
"genericAuthType": "httpHeaderAuth",
"bodyParametersJson": "={\"filter\":{\"callIds\":[\"{{ $json['calldata[0].calls'].id }}\"]}}"
},
"credentials": {
"httpHeaderAuth": {
"name": "<your credential>"
}
},
"typeVersion": 2
},
{
"id": "a9643d2c-6245-4c40-92ee-49eb667e3348",
"name": "Join Transcript to String",
"type": "n8n-nodes-base.set",
"position": [
260,
-140
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "c9828e0c-fce4-487d-b5cb-bff625cb7c8e",
"name": "Conversation",
"type": "array",
"value": "={{ $jmespath($json.body.callTranscripts, '[].transcript[].{\"speaker\": speakerId, \"text\": sentences[].text}') }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "ce7cce2a-95b2-4d74-865d-d1af028e16de",
"name": "Isolate Notion Data",
"type": "n8n-nodes-base.set",
"position": [
2720,
-100
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "ee14c39a-1590-4262-b5ab-36640a6e3c31",
"name": "metaData.CompanyName",
"type": "string",
"value": "={{ $json.sfOpp[0].Name }}"
},
{
"id": "0d323985-076c-456f-bf4c-d9520b07f73d",
"name": "Attendees.internal",
"type": "array",
"value": "={{ $jmespath($json.gongData[0].parties, '[?affiliation==`Internal`].emailAddress') }}"
},
{
"id": "ee040180-fce4-4d68-a406-26a88a383c14",
"name": "metaData.title",
"type": "string",
"value": "={{ $json.gongData[0].metaData.title }}"
},
{
"id": "dea503f9-d575-4804-bbe7-0dcf7d5fbea4",
"name": "metaData.started",
"type": "string",
"value": "={{ $json.gongData[0].metaData.started }}"
},
{
"id": "91fa2545-6a02-43e6-b893-4d3133540a5c",
"name": "metaData.GongCallID",
"type": "string",
"value": "={{ $json.gongData[0].metaData.id }}"
},
{
"id": "c0cbfa8b-40d1-4838-a375-88ea8eb85170",
"name": "metaData.url",
"type": "string",
"value": "={{ $json.gongData[0].metaData.url }}"
},
{
"id": "d10a0184-f17c-4fd6-aed5-72656e15f856",
"name": "Conversation",
"type": "string",
"value": "={{ $json.gongData[0].conversationText }}"
},
{
"id": "02eb0113-7e52-4931-bd10-3f2bee87d984",
"name": "Attendees.external",
"type": "array",
"value": "={{ $jmespath($json.gongData[0].parties, '[?affiliation==`External` || affiliation==`Unknown`].emailAddress') }}"
},
{
"id": "c2183c7b-d552-4a16-bb08-c9ed247f8111",
"name": "Attendees.externalNames",
"type": "array",
"value": "={{ $jmespath($json.gongData[0].parties, '[?affiliation==`External` || affiliation==`Unknown`].name') }}"
},
{
"id": "a232bd40-ae56-4c12-8b3f-9062d4880415",
"name": "Attendees.internalNames",
"type": "array",
"value": "={{ $jmespath($json.gongData[0].parties, '[?affiliation==`Internal`].name') }}"
},
{
"id": "99f7143e-af6c-45d2-b3a1-c5169c6632eb",
"name": "metaData.Integrations",
"type": "string",
"value": "={{ $('Execute Workflow Trigger').item.json['calldata[1].integrations'] }}"
},
{
"id": "7fe14a89-5fda-4594-8b5a-6fbd8a519db9",
"name": "metaData.Competitors",
"type": "string",
"value": "={{ $('Execute Workflow Trigger').item.json['calldata[2].competitors'] }}"
},
{
"id": "29fb3dbe-071c-4b02-9dd9-afa4c3a4ad8f",
"name": "metaData.domain",
"type": "string",
"value": "={{ \n (() => {\n // List of known free email domains\n const freeEmailDomains = [\n 'gmail.com',\n 'yahoo.com',\n 'hotmail.com',\n 'outlook.com',\n 'aol.com',\n 'icloud.com',\n 'mail.com',\n 'yandex.com',\n 'protonmail.com'\n ];\n\n // Extract email addresses using JMESPath\n const emailAddresses = $jmespath($json.gongData[0].parties, '[?affiliation==`External` || affiliation==`Unknown`].emailAddress');\n\n // Function to extract the domain from an email address\n const extractDomain = (email) => email.match(/@([\\w.-]+)/)?.[1];\n\n // Filter out free email domains\n const companyDomains = emailAddresses\n .map(extractDomain)\n .filter(domain => domain && !freeEmailDomains.includes(domain.toLowerCase()));\n\n // Return the first non-free domain or \"Unknown\" if none are found\n return companyDomains[0] || 'Unknown';\n })()\n}}"
},
{
"id": "b28eb61e-6052-4022-9d31-447dbf877982",
"name": "sfOpp",
"type": "array",
"value": "={{ $json.sfOpp }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "38574bd1-82f3-4499-9369-9241e41b35d1",
"name": "Join Affiliation",
"type": "n8n-nodes-base.code",
"position": [
740,
-120
],
"parameters": {
"jsCode": "// Retrieve input data from all items\nconst inputData = $input.all();\nconst originalJson = inputData[0].json; // Get the original JSON data\nconst conversation = originalJson.Conversation;\nconst parties = originalJson.parties;\n\n// Create a mapping of speakerId to affiliation\nconst affiliationMap = {};\nparties.forEach(party => {\n affiliationMap[party.speakerId] = party.affiliation;\n});\n\n// Replace speakerId with affiliation in the conversation data\nconst updatedConversation = conversation.map(entry => {\n const affiliation = affiliationMap[entry.speaker] || 'Unknown'; // Fallback to 'Unknown' if not found\n return {\n ...entry,\n speaker: affiliation, // Replace speakerId with affiliation\n };\n});\n\n// Return the updated conversation along with the original JSON data\nreturn [{ json: { ...originalJson, updatedConversation } }];\n"
},
"typeVersion": 2
},
{
"id": "15809205-cb1d-4d83-8c67-35ab486071b2",
"name": "Join conversation",
"type": "n8n-nodes-base.code",
"position": [
940,
-120
],
"parameters": {
"jsCode": "// Retrieve the original JSON data\nconst originalJson = $json;\nconst conversation = originalJson.updatedConversation;\n\n// Create an array to hold the formatted lines\nconst formattedLines = [];\n\n// Iterate over each entry in the conversation\nconversation.forEach(entry => {\n const speaker = entry.speaker;\n const texts = entry.text;\n\n // Iterate over each text item and format it as \"speaker: text\"\n texts.forEach(line => {\n formattedLines.push(`${speaker}: ${line}`);\n });\n});\n\n// Join the formatted lines with newline characters\nconst result = formattedLines.join('\\n');\n\n// Return the original JSON data along with the new conversationText field\nreturn [{ json: { ...originalJson, conversationText: result } }];\n"
},
"typeVersion": 2
},
{
"id": "1ac9e862-ddf2-4cd5-9339-c69061182231",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
-600,
-500
],
"parameters": {
"width": 340,
"height": 820,
"content": "\n## CallForge - The AI Gong Sales Call Processor\nCallForge allows you to extract important information for different departments from your Sales Gong Calls. \n\n### Transcript PreProcessor\nThis workflow preps the call transcripts to pass into the call processor. It starts by using the code node to separate the different speakers into either Internal or External speaker. It also pulls data from Salesforce to enrich the call data by pulling things such as company name. "
},
"typeVersion": 1
},
{
"id": "7d8f99e2-13c7-4bf2-becc-c7b5c663028d",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-240,
-340
],
"parameters": {
"color": 7,
"width": 720,
"height": 660,
"content": "## Get Gong Transcript and Call Details\nThe transcript is to pass into the AI prompt, but needs to be transformed first. The Call details provide the Prompt with metadata."
},
"typeVersion": 1
},
{
"id": "1454276d-46e6-40b2-9494-c9c380f3eaa1",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
500,
-340
],
"parameters": {
"color": 7,
"width": 580,
"height": 660,
"content": "## Format Call Transcript \nHere we join the call transcript together and then set the speaker as either Internal (for our sales team) or External (for our customers). "
},
"typeVersion": 1
},
{
"id": "d7fa6f56-8234-4995-b559-4809095efcb4",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
1100,
-340
],
"parameters": {
"color": 7,
"width": 1320,
"height": 780,
"content": "## Enrich Call Data\nHere we get the Pipedrive ID using the email domain and use that to search pipedrive for the customer. We also pass the domain into the People Data Labs api to get location data. "
},
"typeVersion": 1
},
{
"id": "b5274357-4e45-4d8b-938d-b3c66f98c82f",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
2440,
-340
],
"parameters": {
"color": 7,
"width": 480,
"height": 660,
"content": "## Extract Final Data Blob\nHere we merge the final outputs and get rid of anything we don't need for the final AI prompt. "
},
"typeVersion": 1
},
{
"id": "a940a941-f9e2-4449-895f-3268e2203a1e",
"name": "Extract SF Opp Data",
"type": "n8n-nodes-base.set",
"position": [
1700,
80
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "64f7f8ec-3c1c-4743-9e5b-6bb5d385e9d2",
"name": "SFOppId",
"type": "string",
"value": "={{ $json.Id }}"
},
{
"id": "85629904-617a-4a5f-87a3-72f2349cdf99",
"name": "OppType",
"type": "string",
"value": "={{ $json.Type }}"
},
{
"id": "f6ec091d-0784-4000-ad49-3bb6ece375ca",
"name": "LeadSource",
"type": "string",
"value": "={{ $json.LeadSource }}"
},
{
"id": "a3fd520e-3577-4c2d-a09a-ad3bc76e0bd7",
"name": "IsClosed",
"type": "boolean",
"value": "={{ $json.IsClosed }}"
},
{
"id": "8a1fac85-5f1b-4ab2-86ea-586df1e2af2b",
"name": "IsWon",
"type": "boolean",
"value": "={{ $json.IsWon }}"
},
{
"id": "0f86f2a2-94bb-412a-b831-974f2528fca3",
"name": "sfStage",
"type": "string",
"value": "={{ $json.StageName }}"
},
{
"id": "f455d38b-d48a-483c-b0d9-def9514741ef",
"name": "companyAccountId",
"type": "string",
"value": "={{ $json.AccountId }}"
},
{
"id": "1eb560db-3dd8-46cb-993d-0e370e25222f",
"name": "usingn8n",
"type": "string",
"value": "={{ $json.n8n_experience__c }}"
},
{
"id": "e1d251e3-40e5-4b63-bbc3-c45e503bb108",
"name": "ForecastCategory",
"type": "string",
"value": "={{ $json.ForecastCategory }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "0b2b5078-96b5-423c-82d1-278f013ecdff",
"name": "Extract SF Opp Data1",
"type": "n8n-nodes-base.set",
"position": [
1880,
260
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "261c0f53-82d1-4deb-ae52-09ea342d0f88",
"name": "Employees",
"type": "string",
"value": "={{ $json.Employees_Bucket__c }}"
},
{
"id": "ca1c9890-4a7d-43c6-b7ad-bf1d522574a7",
"name": "Name",
"type": "string",
"value": "={{ $json.Name }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "fec915a1-10ea-4be6-a15f-cea0ae837633",
"name": "Get Opp Data",
"type": "n8n-nodes-base.salesforce",
"position": [
1460,
80
],
"parameters": {
"resource": "opportunity",
"operation": "get",
"opportunityId": "={{ $('Execute Workflow Trigger').item.json[\"calldata[0].calls\"].sfOpp }}"
},
"credentials": {
"salesforceOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "793127ea-d1c7-4f29-a536-c87ece9d6601",
"name": "Get account data",
"type": "n8n-nodes-base.salesforce",
"position": [
1700,
260
],
"parameters": {
"resource": "account",
"accountId": "={{ $json.AccountId }}",
"operation": "get"
},
"credentials": {
"salesforceOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "249ef11d-47b3-415c-aac0-13437c1fd5c8",
"name": "Extract Call Data",
"type": "n8n-nodes-base.splitOut",
"position": [
260,
40
],
"parameters": {
"options": {},
"fieldToSplitOut": "body.calls"
},
"typeVersion": 1
},
{
"id": "a572d7e8-6613-4f46-8abf-9a254f22cfc1",
"name": "Merge call and transcript Data",
"type": "n8n-nodes-base.merge",
"position": [
540,
-120
],
"parameters": {
"mode": "combine",
"options": {},
"combineBy": "combineByPosition"
},
"typeVersion": 3
},
{
"id": "1bcbafc1-5ef5-43a4-af2a-9689888fc086",
"name": "Aggregate Gong Call Transcript",
"type": "n8n-nodes-base.aggregate",
"position": [
1720,
-120
],
"parameters": {
"options": {},
"aggregate": "aggregateAllItemData",
"destinationFieldName": "gongData"
},
"typeVersion": 1
},
{
"id": "df307a52-512d-4397-8d22-a8a51a06fe21",
"name": "Get External Attendees Emails",
"type": "n8n-nodes-base.set",
"position": [
1280,
80
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "0a813814-2e7d-40e0-961f-ba59baf5ece5",
"name": "externalAttendees",
"type": "array",
"value": "={{ $jmespath($json.parties, '[?affiliation==`External` || affiliation==`Unknown`].emailAddress') }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "a4c7450e-5ad6-4e2f-ab72-0f56ae1390c1",
"name": "Combine Salesforce Opp Data",
"type": "n8n-nodes-base.merge",
"position": [
2060,
100
],
"parameters": {
"mode": "combine",
"options": {},
"combineBy": "combineByPosition"
},
"typeVersion": 3
},
{
"id": "8c201ee7-16f7-4c05-8f6c-d3543c4445e0",
"name": "Aggregate Salesforce data",
"type": "n8n-nodes-base.aggregate",
"position": [
2260,
100
],
"parameters": {
"options": {},
"aggregate": "aggregateAllItemData",
"destinationFieldName": "sfOpp"
},
"typeVersion": 1
},
{
"id": "735173b9-cec1-43b3-94c5-13dc368473dd",
"name": "Merge Enriched Transcript Data",
"type": "n8n-nodes-base.merge",
"position": [
2520,
-100
],
"parameters": {
"mode": "combine",
"options": {},
"combineBy": "combineByPosition"
},
"typeVersion": 3
}
],
"connections": {
"Get Opp Data": {
"main": [
[
{
"node": "Extract SF Opp Data",
"type": "main",
"index": 0
},
{
"node": "Get account data",
"type": "main",
"index": 0
}
]
]
},
"Get transcript": {
"main": [
[
{
"node": "Join Transcript to String",
"type": "main",
"index": 0
}
]
]
},
"Get account data": {
"main": [
[
{
"node": "Extract SF Opp Data1",
"type": "main",
"index": 0
}
]
]
},
"Join Affiliation": {
"main": [
[
{
"node": "Join conversation",
"type": "main",
"index": 0
}
]
]
},
"Extract Call Data": {
"main": [
[
{
"node": "Merge call and transcript Data",
"type": "main",
"index": 1
}
]
]
},
"Join conversation": {
"main": [
[
{
"node": "Get External Attendees Emails",
"type": "main",
"index": 0
},
{
"node": "Aggregate Gong Call Transcript",
"type": "main",
"index": 0
}
]
]
},
"Extract SF Opp Data": {
"main": [
[
{
"node": "Combine Salesforce Opp Data",
"type": "main",
"index": 0
}
]
]
},
"Extract SF Opp Data1": {
"main": [
[
{
"node": "Combine Salesforce Opp Data",
"type": "main",
"index": 1
}
]
]
},
"Execute Workflow Trigger": {
"main": [
[
{
"node": "Get transcript",
"type": "main",
"index": 0
},
{
"node": "Retrieve detailed call data",
"type": "main",
"index": 0
}
]
]
},
"Aggregate Salesforce data": {
"main": [
[
{
"node": "Merge Enriched Transcript Data",
"type": "main",
"index": 1
}
]
]
},
"Join Transcript to String": {
"main": [
[
{
"node": "Merge call and transcript Data",
"type": "main",
"index": 0
}
]
]
},
"Combine Salesforce Opp Data": {
"main": [
[
{
"node": "Aggregate Salesforce data",
"type": "main",
"index": 0
}
]
]
},
"Retrieve detailed call data": {
"main": [
[
{
"node": "Extract Call Data",
"type": "main",
"index": 0
}
]
]
},
"Get External Attendees Emails": {
"main": [
[
{
"node": "Get Opp Data",
"type": "main",
"index": 0
}
]
]
},
"Aggregate Gong Call Transcript": {
"main": [
[
{
"node": "Merge Enriched Transcript Data",
"type": "main",
"index": 0
}
]
]
},
"Merge Enriched Transcript Data": {
"main": [
[
{
"node": "Isolate Notion Data",
"type": "main",
"index": 0
}
]
]
},
"Merge call and transcript Data": {
"main": [
[
{
"node": "Join Affiliation",
"type": "main",
"index": 0
}
]
]
}
}
}
Credentials you'll need
Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.
httpHeaderAuthsalesforceOAuth2Api
Pro
For the full experience including quality scoring and batch install features for each workflow upgrade to Pro
How this works
This workflow streamlines the extraction of key insights from call transcripts by automatically retrieving and processing conversation data, saving you hours of manual review and ensuring accurate capture of client details like affiliations and Notion references. It's ideal for sales or support teams handling high volumes of customer interactions, particularly those integrated with Salesforce for CRM updates. The core step involves joining and isolating transcript elements through targeted code nodes, transforming raw data into structured outputs ready for your systems.
Use this workflow when you need to parse event-triggered call data for immediate Salesforce logging, such as post-call analysis in a busy telesales environment. Avoid it for simple note-taking without transcripts or when dealing with non-audio sources like emails. Common variations include adding email notifications via additional HTTP requests or customising code joins for specific data fields like sentiment scores.
About this workflow
Splitout Code. Uses executeWorkflowTrigger, httpRequest, stickyNote, salesforce. Event-driven trigger; 23 nodes.
Source: https://github.com/Zie619/n8n-workflows — original creator credit. Request a take-down →
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Deep Research old(fr). Uses outputParserStructured, formTrigger, chainLlm, form. Event-driven trigger; 79 nodes.
Output Parser Structured, Form Trigger, Chain Llm +6
Deep Research old(fr). Uses outputParserStructured, formTrigger, chainLlm, form. Event-driven trigger; 79 nodes.
Output Parser Structured, Form Trigger, Chain Llm +6