Receive Call Data and standardize User Prompt
Configured with Agent, Aggregate, Execute Workflow, Execute Workflow Trigger, and additional nodes. Review the connections and setup before adapting this template.
Node categories in this workflow
- Trigger
- Transform
- AI & models
- Subworkflow
Icons describe general node roles, inferred from node types. Inspect the parameters for the configured action.
Drag to pan; use + and − to zoom. Reconstructed from the exported node positions; nothing runs here. Dashed lines represent non-main connections. Full node names and notes appear below.
How it works
The exported workflow contains the following configured nodes. Their connections are shown above; inspect the JSON for the complete logic, expressions, and external actions.
| Node | Category | Type | Operation |
|---|---|---|---|
| Execute Workflow Trigger | Trigger | Execute Workflow Trigger | See node parameters |
| Structured Output Parser1 | Transform | Output Parser Structured | See node parameters |
| Marketing AI Agent Processor | AI & models | Agent | See node parameters |
| Structured Output Parser2 | Transform | Output Parser Structured | See node parameters |
| Product AI Agent Processor | AI & models | Agent | See node parameters |
| Sales Data Processor | Subworkflow | Execute Workflow | See node parameters |
| Marketing Data Processor | Subworkflow | Execute Workflow | See node parameters |
| Product AI Data Processor | Subworkflow | Execute Workflow | See node parameters |
| Data Recall Sales | Transform | Edit Fields | See node parameters |
| Data Recall Marketing | Transform | Edit Fields | See node parameters |
| Data Recall Product | Transform | Edit Fields | See node parameters |
| SF Sales Data Processor | Subworkflow | Execute Workflow | See node parameters |
| Azure OpenAI Chat Model | AI & models | LM Chat Azure Open Ai | See node parameters |
| Azure OpenAI Chat Model1 | AI & models | LM Chat Azure Open Ai | See node parameters |
| Azure OpenAI Chat Model2 | AI & models | LM Chat Azure Open Ai | See node parameters |
| Create User Prompt | Transform | Edit Fields | See node parameters |
| Success Status Generated | Transform | Edit Fields | See node parameters |
| AI Agent | AI & models | Agent | See node parameters |
| Structured Output Parser3 | Transform | Output Parser Structured | See node parameters |
| Merge all processed data | Transform | Merge | See node parameters |
| Bundle processed Data | Transform | Aggregate | See node parameters |
Setup
- Download the JSON and import it into an isolated n8n instance. Leave the workflow inactive.
- Connect your own credentials through n8n’s credential store. Replace
REPLACE_WITH_*values with your resource identifiers. - Inspect API destinations, Code nodes, database queries, file paths, and outbound actions.
- Run with synthetic data and harmless destinations. Enable triggers only after checking the actual outputs.
Requirements
An n8n instance with the listed node types and compatible versions. Service-connected workflows may require accounts, credentials, or paid APIs.
Credential types declared in the source
azureOpenAiApi
Workflow notes
Receive Call Data and standardize User Prompt
Receive Call Data and standardize User Prompt
This node gets the call data passed into it, and it creates a single user prompt that is passed into all 3 AI agents. This allows for standardizing things such as name misprononciation and integration data to be set in one node that can easily be updated and automatically be sent to the 3 AI agents.
CallForge - The AI Gong Sales Call Processor
CallForge - The AI Gong Sales Call Processor
CallForge allows you to extract important information for different departments from your Sales Gong Calls.
AI Agent Processor
This is where the AI magic happens. In this workflow, we take the final transcript blog and pass it into the AI Prompt for analysis and data extraction.
Process Sales Agent
Process Sales Agent
The Sales agent structured output is passed to both the notion processor and the Salesforce processor, thereby feeding the data back to the main platform where the sales team works.
Process Marketing Agent
Process Marketing Agent
The marketing agent outputs to a subworkflow that feeds to a notion database.
Process Product Agent
Process Product Agent
The product team also uses notion so the output is fed to a subworkflow that outputs to Notion as well.
Process Queue Logic
Process Queue Logic
If the run fails for any reason, it can be rerun on only the remaining calls, allowing for greater resilisience in api calls. The main issue I ran into was Notion rate limiting.
Receive Call Data and standardize User Prompt
Receive Call Data and standardize User Prompt
Purpose and structure
This folder contains the Receive Call Data and standardize User Prompt workflow. Its executable nodes use agent, aggregate, executeWorkflow, executeWorkflowTrigger, lmChatAzureOpenAi, merge, outputParserStructured, set. The table and connection map below are derived from the JSON, not an inferred guarantee of behavior.
Setup
Import inactive. Configure your own credentials and replace REPLACE_WITH_* values. Review external destinations and Code nodes before running.
Entry points
Execute Workflow Trigger
Verification
Sanitized source candidate; not runtime-tested. This overview is generated from node metadata. Read the folder README for the connection map, credential types, and license.
Attribution
https://github.com/Zie619/n8n-workflows/blob/94007c1445d9258a7da116646b79473e7c7c3282/workflows/Aggregate/0762_Aggregate_Stickynote_Create_Triggered.json MIT; preserve source notices.