AI Powered Client Support System

A growing support ticket volume needed faster first response and consistent triage without proportionally growing the support team.

1. 01
   Ticket intake

   Incoming support tickets are captured through the helpdesk platform as usual.

2. 02
   AI triage and drafting

   An automation sends ticket content to an AI model, which classifies the ticket and drafts a suggested response or routing decision.

3. 03
   Context logging

   Ticket history and context are logged centrally, so repeat contacts and prior resolutions inform future responses.

4. 04
   Human review layer

   Support staff review AI drafted responses before sending (or the system escalates directly to a human for complex tickets), keeping quality control in place.

Originally built for the agency ops, the same architecture applies to any team facing a similar volume, compliance, or coordination problem. The stack (Freshdesk, Claude API, n8n, and others) is stable, self hosted where it matters, and designed to be operated by a small team without a platform crew.

• AI support ticketing automation
• AI helpdesk automation
• Claude API customer support automation

• FreshdeskPart of the production stack for this build.
• Claude APIReasoning and structured outputs. The default LLM for anything that needs to be trusted in production.
• n8nWorkflow runtime and orchestration. Every scheduled job, webhook, and branch lives here so the logic is version controlled and observable.
• SupabasePostgres, auth, and storage. Holds the source of truth for records the workflows read and write.

Next time I would formalise the internal ops as small SaaS style surfaces earlier, rather than composing n8n and Airtable. It ages better as the agency grows headcount.

Using Claude to triage support tickets before a human ever sees them. Good practical build log style content.