Top Cars Sales Agent.
Engineering case study by Priyansh Dobariya · n8n · GoHighLevel · Google Docs · OpenAI
A lead conversation with product context.
An n8n workflow that routes automotive-service questions to specialized agents and connects replies with CRM history and service documents.
Behind the build.
Webhook-led conversation intake
Service-specific sub-workflows
CRM notes and escalation
Tools & technologies
What this solves
Vehicle-service leads ask about different products, prices, warranties, and availability. A single static reply loses the vehicle and conversation context needed to answer usefully.
How it works
The main n8n webhook normalizes inbound messages and retrieves GoHighLevel notes and conversation history. An AI agent can call separate n8n sub-workflows for wrap and PPF, ceramic coating, tint, availability, warranty, and objection handling. Google Docs tools supply service reference material; HTTP nodes write CRM updates.
From input to outcome
An inbound message reaches the webhook, is classified with customer and vehicle context, and goes to a product-specific workflow when needed. Structured output and conditional nodes determine the reply and whether CRM details or notes should be updated. Off-hours and escalation branches change the route.
Decisions visible in the code
- Specialist sub-workflows keep service-specific knowledge and response logic separate from the conversation coordinator.
- CRM context is fetched before response generation so repeated questions can use earlier notes rather than start from zero.
What the workflow enables
The workflow can turn a broad sales inquiry into a context-aware response and a recorded CRM handoff.
Workflow exports demonstrate configured nodes; they do not establish conversion gains or complete live reliability.