AutomationFlowsAI & RAG › AI Automation Consultant with Google Gemini

AI Automation Consultant with Google Gemini

Original n8n title: AI Automation Consultant

Ai Automation Consultant. Uses lmChatGoogleGemini, agent. Webhook trigger; 4 nodes.

Webhook trigger★★☆☆☆ complexityAI-powered4 nodesGoogle Gemini ChatAgent
AI & RAG Trigger: Webhook Nodes: 4 Complexity: ★★☆☆☆ AI nodes: yes Added:

This workflow follows the Agent → Google Gemini Chat recipe pattern — see all workflows that pair these two integrations.

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 →

Download .json
{
  "nodes": [
    {
      "parameters": {
        "httpMethod": "POST",
        "path": "consultant",
        "responseMode": "responseNode",
        "options": {
          "allowedOrigins": "*"
        }
      },
      "type": "n8n-nodes-base.webhook",
      "typeVersion": 1,
      "position": [
        -240,
        -32
      ],
      "id": "e3650676-f3b7-4057-8321-0102caf367c2",
      "name": "Webhook Trigger"
    },
    {
      "parameters": {
        "options": {}
      },
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "typeVersion": 1,
      "position": [
        -80,
        176
      ],
      "id": "a38d9fab-79a6-40d1-b48c-78cec429fd79",
      "name": "Google Gemini Chat Model",
      "credentials": {
        "googlePalmApi": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {
        "respondWith": "json",
        "responseBody": "={{ $json.output }}",
        "options": {
          "responseHeaders": {
            "entries": [
              {
                "name": "Access-Control-Allow-Origin",
                "value": "*"
              }
            ]
          }
        }
      },
      "type": "n8n-nodes-base.respondToWebhook",
      "typeVersion": 1,
      "position": [
        352,
        -32
      ],
      "id": "0a67b4ab-4b38-4255-8f11-1f146bddbad7",
      "name": "Respond to Webhook"
    },
    {
      "parameters": {
        "promptType": "define",
        "text": "={{\n'CLIENT INTAKE FORM DATA:\\n' +\n'------------------------\\n' +\n'Industry: ' + $json.body.industry + '\\n' +\n'User Role: ' + $json.body.role + '\\n' +\n'Manual Process (The Problem): ' + $json.body.manual_task + '\\n' +\n'Current Tech Stack: ' + $json.body.tools + '\\n' +\n'Trigger Event: ' + $json.body.trigger + '\\n' +\n'Desired Outcome: ' + $json.body.goal + '\\n' +\n'------------------------\\n\\n' +\n'Based on this intake, design a complete automation architecture.'\n}}",
        "hasOutputParser": true,
        "options": {
          "systemMessage": "Role: Senior Automation Architect & n8n Solutions Expert.\n\n**Goal:**\nYou are a high-end consultant. A client has described a manual, painful business process. You must analyze their specific stack and architect a robust n8n workflow to solve it.\n\n**Consulting Rules:**\n1. **Analyze the Stack:** Look at the \"Current Tech Stack\". If they list generic names (e.g., \"Email\", \"Spreadsheet\"), you MUST pick the most standard specific tool (e.g., \"Gmail\", \"Google Sheets\") for the blueprint.\n2. **Fill the Gaps:** If they want to \"Send an SMS\" but didn't list an SMS tool, YOU must recommend one (e.g., \"Twilio\").\n3. **Be Technical:** The workflow steps must be logical. Start with the specific Trigger -> Process Data -> End with the Action.\n\n**Output Schema (Strict JSON):**\nYou must output ONLY JSON. Do not include markdown formatting. Use this exact structure:\n\n{{\n  \"industry\": \"Client's Industry\",\n  \"business_name\": \"A creative name for their business type\",\n  \"pain_point\": \"A summary of the manual bottleneck\",\n  \"solution_title\": \"Professional Name for the Automation\",\n  \"solution_description\": \"2-3 sentences explaining the value.\",\n  \"workflow_steps\": [\n    {{ \"step\": 1, \"tool\": \"Exact Tool Name (e.g. Typeform)\", \"action\": \"Specific technical action (e.g. Trigger on new submission)\" }},\n    {{ \"step\": 2, \"tool\": \"n8n\", \"action\": \"Format data structure\" }}\n  ],\n  \"saas_stack\": [\n    {{ \"name\": \"Tool Name\", \"role\": \"What it does in this flow\", \"type\": \"Native\" or \"HTTP\" }}\n  ]\n}}"
        }
      },
      "type": "@n8n/n8n-nodes-langchain.agent",
      "typeVersion": 3,
      "position": [
        0,
        -32
      ],
      "id": "94cd129d-742b-4eea-b666-00aab19ff14d",
      "name": "AI Agent"
    }
  ],
  "connections": {
    "Webhook Trigger": {
      "main": [
        [
          {
            "node": "AI Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Google Gemini Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "AI Agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "AI Agent": {
      "main": [
        [
          {
            "node": "Respond to Webhook",
            "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.

Pro

For the full experience including quality scoring and batch install features for each workflow upgrade to Pro

About this workflow

Ai Automation Consultant. Uses lmChatGoogleGemini, agent. Webhook trigger; 4 nodes.

Source: https://github.com/Victor7092/ai-automation-consultant/blob/main/workflow.json — original creator credit. Request a take-down →

More AI & RAG workflows → · Browse all categories →

Related workflows

Workflows that share integrations, category, or trigger type with this one. All free to copy and import.

AI & RAG

Workflow Hcmute. Uses agent, lmChatGoogleGemini, memoryBufferWindow, googleSheetsTool. Webhook trigger; 13 nodes.

Agent, Google Gemini Chat, Memory Buffer Window +2
AI & RAG

N8N Workflow. Uses httpRequest, toolHttpRequest, memoryBufferWindow, lmChatGoogleGemini. Webhook trigger; 13 nodes.

HTTP Request, Tool Http Request, Memory Buffer Window +2
AI & RAG

This workflow automatically turns any YouTube video into a structured blog post with Gemini AI. By sending a simple POST request with a YouTube URL to a webhook, it downloads the video’s audio, transc

Agent, Google Gemini Chat, Output Parser Structured +3
AI & RAG

Ai Summarizer. Uses agent, lmChatGoogleGemini, lmChatOllama, httpRequestTool. Webhook trigger; 11 nodes.

Agent, Google Gemini Chat, Ollama Chat +1
AI & RAG

This workflow contains community nodes that are only compatible with the self-hosted version of n8n.

Google Calendar Tool, Tool Think, Google Gemini Chat +3