Automate Restaurant Sales & Inventory Forecasting with Gemini AI & Google Sheets

The workflow JSON

Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →

{
  "id": "Y6Pn9PLNoMU7e8Xb",
  "meta": {
    "templateCredsSetupCompleted": true
  },
  "name": "Restaurant Sales & Inventory Forecasting System using Gemini AI & Google Sheets",
  "tags": [],
  "nodes": [
    {
      "id": "80bda799-9bcd-41b5-a94e-ab32919b04e3",
      "name": "Workflow Explanation",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        140,
        -200
      ],
      "parameters": {
        "color": 4,
        "width": 740,
        "height": 200,
        "content": "## Workflow Overview \n\n### This workflow automates weekly forecasting of restaurant sales and raw material requirements using historical data from Google Sheets and AI predictions powered by Google Gemini. The forecast is then emailed to stakeholders for efficient planning and waste reduction."
      },
      "typeVersion": 1
    },
    {
      "id": "848c741c-7206-46cb-b10e-205feb126544",
      "name": "Trigger Weekly Forecast",
      "type": "n8n-nodes-base.scheduleTrigger",
      "position": [
        -340,
        460
      ],
      "parameters": {
        "rule": {
          "interval": [
            {
              "field": "weeks",
              "triggerAtHour": 20
            }
          ]
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "75c05f50-aea8-48d7-ae9c-fc1e9af03179",
      "name": "Load Historical Sales Data",
      "type": "n8n-nodes-base.googleSheets",
      "position": [
        -120,
        460
      ],
      "parameters": {
        "options": {},
        "sheetName": {
          "__rl": true,
          "mode": "list",
          "value": "gid=0",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1QZXX_gjNTTZ0vqPozNysjASQS3UcgwwWVpYvN7r-T_I/edit#gid=0",
          "cachedResultName": "current data"
        },
        "documentId": {
          "__rl": true,
          "mode": "list",
          "value": "1QZXX_gjNTTZ0vqPozNysjASQS3UcgwwWVpYvN7r-T_I",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1QZXX_gjNTTZ0vqPozNysjASQS3UcgwwWVpYvN7r-T_I/edit?usp=drivesdk",
          "cachedResultName": "Restaurant stock predictions"
        },
        "authentication": "serviceAccount"
      },
      "credentials": {
        "googleApi": {
          "name": "<your credential>"
        }
      },
      "typeVersion": 4.6
    },
    {
      "id": "ecbf01be-4691-4a9e-b4dd-312a96ba73b2",
      "name": "Format Input for AI Agent",
      "type": "n8n-nodes-base.code",
      "position": [
        100,
        460
      ],
      "parameters": {
        "jsCode": "// Fetch all incoming items\nconst items = $input.all();\n\n// Extract the raw row data (each item.json is one row)\nconst rawRows = items.map(item => item.json);\n\n// Bundle everything into a single field\nconst payload = { rows: rawRows };\n\n// Return a single output item whose json contains your full dataset\nreturn [{ json: { data: payload } }];\n"
      },
      "typeVersion": 2
    },
    {
      "id": "b83e66e4-2d98-47e0-9fb6-e5837863494e",
      "name": "Generate Forecast with AI",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        320,
        460
      ],
      "parameters": {
        "text": "={{ $json.data }}",
        "options": {
          "systemMessage": "You are a restaurant demand forecasting assistant.\n\nYou will be given a JSON object 'data' containing an array of historical weekly records. Each record includes:\n- row_number\n- Date (ISO format)\n- Sales for dishes (e.g. \"Neapolitan Pizza Sold\", \"Picanha Sold\", etc.)\n- Quantities of raw materials used that week (e.g. \"Flour (kg)\", \"Cheese (kg)\", etc.)\n\nYour task:\n1. Analyze trends across the historical weeks.\n2. Forecast next Monday\u2019s sales (units sold for each dish).\n3. Calculate the required quantity of each raw material needed next week to match that forecast, based on per\u2011unit usage rates inferred from the data.\n4. Output exactly one JSON record, following the same structure as the input records. For example:\n\n```json\n{\n  \"row_number\": 7,\n  \"Date\": \"2025-07-14\",\n  \"Neapolitan Pizza Sold\": 58,\n  \"Picanha Sold\": 36,\n  \"Huevos Rancheros Sold\": 62,\n  \"Japanese Curry Sold\": 48,\n  \"Birria Ramen Sold\": 31,\n  \"Flour (kg)\": 11.5,\n  \"Cheese (kg)\": 5.8,\n  \"Tomato Sauce (L)\": 4.4,\n  \"Beef (kg)\": 18,\n  \"Pork (kg)\": 10,\n  \"Rice (kg)\": 5.8,\n  \"Tortillas (pcs)\": 62,\n  \"Eggs (pcs)\": 62,\n  \"Curry Powder (kg)\": 1.45,\n  \"Chili Powder (kg)\": 1.05\n}\n\nUse think tool if needed\n"
        },
        "promptType": "define"
      },
      "typeVersion": 1.9
    },
    {
      "id": "d0cc88f1-0bdb-48c0-9d6e-ff68e93517f0",
      "name": "AI Think Tool",
      "type": "@n8n/n8n-nodes-langchain.toolThink",
      "position": [
        468,
        680
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "c7df1137-e2b1-4ea9-9dd4-e4025e92480e",
      "name": "Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        348,
        680
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.5-pro"
      },
      "credentials": {
        "googlePalmApi": {
          "name": "<your credential>"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "40dd2b9c-85b4-4e44-8e48-2972fb75645b",
      "name": "Interpret AI Forecast Output",
      "type": "n8n-nodes-base.code",
      "position": [
        696,
        460
      ],
      "parameters": {
        "jsCode": "// Run this in 'Run Once for All Items' mode\n\n// Assume AI agent returned a single item and that its output is in item.json.output\nconst items = $input.all();\nconst aiText = items[0].json.output;\n\n// Remove markdown fences and extract JSON\nconst jsonString = aiText\n  .replace(/```json\\s*([\\s\\S]*?)```/i, '$1') // strip markdown fences\n  .trim();\n\n// Parse it to a JS object\nlet parsed;\ntry {\n  parsed = JSON.parse(jsonString);\n} catch (e) {\n  throw new Error('Failed to parse JSON from AI output: ' + e.message);\n}\n\n// Ready to output\nreturn [{ json: parsed }];\n"
      },
      "typeVersion": 2
    },
    {
      "id": "537236ac-461a-416d-ada7-4e6be84cb790",
      "name": "Log Forecast to Google Sheets",
      "type": "n8n-nodes-base.googleSheets",
      "position": [
        916,
        460
      ],
      "parameters": {
        "columns": {
          "value": {},
          "schema": [
            {
              "id": "Date",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Date",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Neapolitan Pizza Sold",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Neapolitan Pizza Sold",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Picanha Sold",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Picanha Sold",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Huevos Rancheros Sold",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Huevos Rancheros Sold",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Japanese Curry Sold",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Japanese Curry Sold",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Birria Ramen Sold",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Birria Ramen Sold",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Flour (kg)",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Flour (kg)",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Cheese (kg)",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Cheese (kg)",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Tomato Sauce (L)",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Tomato Sauce (L)",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Beef (kg)",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Beef (kg)",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Pork (kg)",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Pork (kg)",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Rice (kg)",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Rice (kg)",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Tortillas (pcs)",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Tortillas (pcs)",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Eggs (pcs)",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Eggs (pcs)",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Curry Powder (kg)",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Curry Powder (kg)",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Chili Powder (kg)",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Chili Powder (kg)",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            }
          ],
          "mappingMode": "autoMapInputData",
          "matchingColumns": [],
          "attemptToConvertTypes": false,
          "convertFieldsToString": false
        },
        "options": {},
        "operation": "append",
        "sheetName": {
          "__rl": true,
          "mode": "list",
          "value": 370915330,
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1QZXX_gjNTTZ0vqPozNysjASQS3UcgwwWVpYvN7r-T_I/edit#gid=370915330",
          "cachedResultName": "prediction data"
        },
        "documentId": {
          "__rl": true,
          "mode": "list",
          "value": "1QZXX_gjNTTZ0vqPozNysjASQS3UcgwwWVpYvN7r-T_I",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1QZXX_gjNTTZ0vqPozNysjASQS3UcgwwWVpYvN7r-T_I/edit?usp=drivesdk",
          "cachedResultName": "Restaurant stock predictions"
        },
        "authentication": "serviceAccount"
      },
      "credentials": {
        "googleApi": {
          "name": "<your credential>"
        }
      },
      "typeVersion": 4.6
    },
    {
      "id": "0af7f39a-aa13-44fc-a653-71533d2851b6",
      "name": "Email Forecast Summary",
      "type": "n8n-nodes-base.gmail",
      "position": [
        1136,
        460
      ],
      "parameters": {
        "sendTo": "user@example.com",
        "message": "=Dear Manager,<br><br>\u00a0 \nPlease find the details for the monday predicted data.<br><br>\u00a0 \n\n\n\n<b>Scraping Date:</b>{{ $json.Date }}<br> \n<br>\u00a0 \n\n\n<b>Sheet link with all data:</b><br> \n<a href=\"https://docs.google.com/spreadsheets/d/1QZXX_gjNTTZ0vqPozNysjASQS3UcgwwWVpYvN7r-T_I/edit?usp=sharing\">Click here to view the data</a><br>\n\n\n\n<br>\u00a0 Thanks,<br> Ajay Mishra",
        "options": {},
        "subject": "Next monday prediction"
      },
      "credentials": {
        "gmailOAuth2": {
          "name": "<your credential>"
        }
      },
      "typeVersion": 2.1
    },
    {
      "id": "761f823d-4ba8-44d3-9ae7-c595de84cf9e",
      "name": "Sticky Note",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -380,
        140
      ],
      "parameters": {
        "width": 180,
        "height": 480,
        "content": "Automatically starts the workflow at a scheduled time."
      },
      "typeVersion": 1
    },
    {
      "id": "aa031a03-5275-4aef-b1e9-a4e54b782a55",
      "name": "Sticky Note1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -160,
        140
      ],
      "parameters": {
        "color": 3,
        "width": 180,
        "height": 480,
        "content": "Pulls weekly sales and material usage from Google Sheets."
      },
      "typeVersion": 1
    },
    {
      "id": "f87f5e45-590f-466e-8869-7d79216ee073",
      "name": "Sticky Note2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        656,
        140
      ],
      "parameters": {
        "color": 2,
        "width": 180,
        "height": 480,
        "content": "Parses the AI's response into readable, usable JSON format."
      },
      "typeVersion": 1
    },
    {
      "id": "d2dfb72b-056a-429c-b1b2-0fd95acea27d",
      "name": "Sticky Note3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        876,
        140
      ],
      "parameters": {
        "color": 5,
        "width": 180,
        "height": 480,
        "content": "Stores the new forecast data back into a Google Sheet."
      },
      "typeVersion": 1
    },
    {
      "id": "c59672c3-2e43-4720-9952-1cca1af8b1ea",
      "name": "Sticky Note4",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1096,
        140
      ],
      "parameters": {
        "color": 3,
        "width": 180,
        "height": 480,
        "content": "Sends a summary of the forecast via Gmail."
      },
      "typeVersion": 1
    },
    {
      "id": "265d61ce-6aad-46ee-a30d-81e291b91bed",
      "name": "Sticky Note5",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        60,
        140
      ],
      "parameters": {
        "color": 4,
        "width": 180,
        "height": 480,
        "content": "Transforms raw data into a structured format suitable for the AI Agent.\n\n"
      },
      "typeVersion": 1
    },
    {
      "id": "ee2932b4-96ec-464f-8b6c-0971a30740e3",
      "name": "Sticky Note6",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        320,
        140
      ],
      "parameters": {
        "color": 6,
        "width": 260,
        "height": 480,
        "content": "Uses Gemini AI to analyze trends and predict upcoming needs."
      },
      "typeVersion": 1
    }
  ],
  "active": false,
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "01083ee7-6a3e-4dd5-92b3-13b38dbc019e",
  "connections": {
    "Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "Generate Forecast with AI",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "AI Think Tool": {
      "ai_tool": [
        [
          {
            "node": "Generate Forecast with AI",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "Trigger Weekly Forecast": {
      "main": [
        [
          {
            "node": "Load Historical Sales Data",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Format Input for AI Agent": {
      "main": [
        [
          {
            "node": "Generate Forecast with AI",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Generate Forecast with AI": {
      "main": [
        [
          {
            "node": "Interpret AI Forecast Output",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Load Historical Sales Data": {
      "main": [
        [
          {
            "node": "Format Input for AI Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Interpret AI Forecast Output": {
      "main": [
        [
          {
            "node": "Log Forecast to Google Sheets",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Log Forecast to Google Sheets": {
      "main": [
        [
          {
            "node": "Email Forecast Summary",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}

Credentials you'll need

Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.

• gmailOAuth2
• googleApi
• googlePalmApi

About this workflow

This automated n8n workflow performs weekly forecasting of restaurant sales and raw material requirements using historical data from Google Sheets and AI predictions powered by Google Gemini. The forecast is then emailed to stakeholders for efficient planning and waste reduction.

Source: https://n8n.io/workflows/5983/ — original creator credit. Request a take-down →

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