You are helping me build the following AI agent workflow.

## Goal
Payment Issue Escalation: Validates reported payment issues against transaction records using AI to prevent false escalations before creating tickets and notifying...

## Specification
- What it does: You stop wasting time on false payment alerts because the AI instantly checks reported issues against your transaction records before creating tickets. It automatically handles valid cases by generating Zendesk tickets and notifying you via Slack while filtering out invalid reports to keep your team focused on real problems.
- Trigger: Triggered by an event (Event · on webhook receipt)
- Autonomy: Fully hands-off
- Expected setup effort: about an afternoon
- Tools/services involved:
  - Webhook: Intake of payment issue data
  - Google Sheets: Transaction lookup and status updates
  - Azure OpenAI Chat Model: AI escalation decision logic
  - Zendesk: Creating support tickets
  - Slack: Logging context and error alerts

## Known pitfalls, handle each one explicitly in your implementation
1. Webhook payloads may contain malformed JSON so add input validation before passing data to the lookup step.
2. Azure OpenAI responses might lack structured output for downstream tools, enforce JSON mode in the model configuration.

## Reference implementation
https://n8n.io/workflows/13178 (workflow template)
Fetch and inspect this before building. If it matches my stack, adapt it;
if not, rebuild the pattern with my tools.

## Process requirements
1. Before building: ask me which of the listed tools I actually use and
   what my platform is (n8n / Make / code / other). Do not assume.
2. Adapt the pattern to my answers; do not force the reference stack.
3. Address every pitfall above; tell me how you handled each.
4. Provide a test plan I can run before letting this touch real data.
5. Ask before any step that sends messages, modifies data, or spends money.

Source: https://usecasesforagents.com/use-case/automate-payment-issue-escalation/ via usecasesforagents.com