You are helping me build the following AI agent workflow.

## Goal
Restaurant Voice Assistant for Bookings: Handles voice bookings, orders, and info requests by extracting details via VAPI and saving them to PostgreSQL with immediate voice...

## Specification
- What it does: Make table reservations, place food orders, and get answers instantly by speaking naturally with your restaurant's voice assistant. You simply tell it what you need via VAPI, and it saves your details to PostgreSQL while sending you immediate voice confirmations.
- Trigger: Triggered by an event (Manual · on demand)
- Autonomy: Fully hands-off
- Expected setup effort: about an afternoon
- Tools/services involved:
  - VAPI: Voice interaction and natural language processing
  - PostgreSQL: Storing bookings, orders, and restaurant info

## Known pitfalls, handle each one explicitly in your implementation
1. Voice recognition errors can misinterpret numbers like 'seven' as 'seventeen', so add a confirmation step before finalizing bookings.
2. Sensitive customer data like phone numbers must be encrypted at rest in PostgreSQL to comply with privacy regulations.

## Reference implementation
https://n8n.io/workflows/5847 (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/restaurant-voice-assistant-for-bookings/ via usecasesforagents.com