Handle restaurant orders from chat and turn them into clean records that your team can use right away. A smart assistant confirms items, quantities, and table number, then logs each item to Google Sheets and hands the order to your POS flow. This helps during rush hours and keeps your front of house moving.

The flow starts when a chat message hits a public webhook. An AI Agent with the OpenAI model and short memory talks with the guest, fixes mistakes, and confirms details. The Information Extractor and a Python Code step pull items, quantities, and table, then build a tidy list. An If check blocks bad input, a loop sends each item to Google Sheets with a timestamp, and a tool node forwards the final text to a subworkflow that prepares the POS steps. A second trigger also lets other workflows feed structured text into the same pipeline.

You need an OpenAI API key and a Google Sheets account with a sheet that has Item, Quantity, Table No, and Timestamp columns. Expect faster intake, fewer typos, and a live log that managers can monitor. It fits small restaurants, pop ups, and teams that capture orders from chat, kiosks, or staff tablets.

• Public chat webhook receives customer messages in real time
• AI Agent with short memory confirms and corrects order details
• OpenAI Chat Model interprets natural language from guests
• Information Extractor uses patterns to find items, quantities, and table
• Python Code node builds a clean JSON list of order items
• If check stops processing when required fields are missing
• Split in Batches sends each item to the sheet one at a time
• Google Sheets append adds rows with a timestamp to your order log
• Call n8n Workflow Tool forwards the order to a POS subworkflow
• Execute Workflow Trigger lets other flows pass in refined order text

• Reduce manual order entry from 15 minutes per shift to under 2 minutes
• Automate more than 90 percent of repetitive logging to the sheet
• Improve data accuracy by standardizing items, quantities, and table numbers
• Handle up to 3 times more order volume during busy hours
• Connect chat intake with Google Sheets and your POS workflow
• See live order activity with timestamps for quick oversight

1. Import the template into n8n: Create a new workflow in n8n > Click the three dots menu > Select 'Import from File' > Choose the downloaded JSON file.
2. You'll need accounts with Google Sheets and OpenAI. See the Tools Required section above for links to create accounts with these services.
3. In the n8n credentials manager, create an OpenAI credential. Choose API Key, paste your key from the OpenAI API page, and give the credential a clear name.
4. In the n8n credentials manager, create a Google Sheets OAuth2 credential. Sign in with the Google account that owns the order log sheet and grant access. Name the credential so your team can identify it later.
5. Open the Google Sheets node and select your Google Sheets credential. Choose the document by URL and select the correct sheet. Map Item, Quantity, Table No, and Timestamp to the matching fields.
6. Open the Chat Trigger node and enable public access. Copy the webhook URL and send a test POST request with a JSON body like {"message": "2 lattes and 1 tea table 4"}.
7. Open the AI Agent node. Review the system message so it matches your brand voice and menu rules. Confirm it is linked to the OpenAI Chat Model node.
8. Open the Information Extractor node. Update the patterns to include your menu items and any common variations. Keep the schema for items, quantity, and table.
9. Open the Code node. Confirm the script outputs a list with item, quantity, and table fields. Adjust field names if your sheet headers differ.
10. Open the Call n8n Workflow Tool node and select the downstream POS workflow. Map the text or structured data that the POS flow expects.
11. Turn on the workflow. Send sample orders and confirm new rows appear in the Google Sheet with the correct timestamp. Check that the POS subworkflow receives the payload.
12. If rows do not appear, check the If node output, verify Google Sheets permissions, and expand the extractor patterns to include the words your guests use.