Mis - Sentinel Intelligence Observer

The workflow JSON

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{
  "name": "MIS - SENTINEL Intelligence Observer",
  "nodes": [
    {
      "parameters": {
        "rule": {
          "interval": [
            {
              "field": "minutes",
              "minutesInterval": 10
            }
          ]
        }
      },
      "id": "schedule-trigger",
      "name": "Schedule - Every 10min",
      "type": "n8n-nodes-base.scheduleTrigger",
      "typeVersion": 1.1,
      "position": [
        250,
        300
      ]
    },
    {
      "parameters": {
        "operation": "executeQuery",
        "query": "SELECT \n  id,\n  created_at,\n  sender_name,\n  sender_phone,\n  sender_type,\n  message_body,\n  sentiment,\n  urgency_score,\n  needs_attention,\n  keywords,\n  is_group_message,\n  group_type,\n  group_name,\n  group_sender_phone,\n  group_sender_name,\n  team_analysis,\n  workflow_name,\n  location_name\nFROM mottivme_intelligence_system.messages\nWHERE processed_by_observer = FALSE\n  AND created_at >= NOW() - INTERVAL '20 minutes'\nORDER BY created_at DESC\nLIMIT 100",
        "options": {}
      },
      "id": "get-unprocessed",
      "name": "Buscar Mensagens N\u00e3o Processadas",
      "type": "n8n-nodes-base.postgres",
      "typeVersion": 2.6,
      "position": [
        450,
        300
      ],
      "credentials": {
        "postgres": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {
        "jsCode": "const items = $input.all();\n\nif (items.length === 0) {\n  return [];\n}\n\n// Agrupa mensagens para an\u00e1lise em batch\nconst context = items.map(item => ({\n  id: item.json.id,\n  timestamp: item.json.created_at,\n  sender: item.json.is_group_message ? item.json.group_sender_name : item.json.sender_name,\n  sender_type: item.json.sender_type,\n  message: item.json.message_body,\n  sentiment: item.json.sentiment,\n  urgency: item.json.urgency_score,\n  keywords: item.json.keywords,\n  workflow: item.json.workflow_name,\n  location: item.json.location_name,\n  team_analysis: item.json.team_analysis\n}));\n\nconst prompt = `Voc\u00ea recebeu ${context.length} mensagens para analisar.\n\nMensagens:\n${JSON.stringify(context, null, 2)}\n\nAnalise essas mensagens e identifique:\n1. Padr\u00f5es de processo (a\u00e7\u00f5es repetidas, sequ\u00eancias)\n2. Decis\u00f5es sendo tomadas\n3. Gargalos operacionais\n4. Conhecimento t\u00e1cito sendo compartilhado\n5. Oportunidades de automa\u00e7\u00e3o\n\nGere insights APENAS se identificar algo significativo (3+ ocorr\u00eancias similares ou algo cr\u00edtico).\nCada insight deve ter evid\u00eancias concretas baseadas nas mensagens.`;\n\nreturn [{\n  json: {\n    prompt: prompt,\n    message_ids: items.map(i => i.json.id),\n    total_messages: items.length,\n    context: context\n  }\n}];"
      },
      "id": "prepare-context",
      "name": "Preparar Contexto para IA",
      "type": "n8n-nodes-base.code",
      "typeVersion": 2,
      "position": [
        650,
        300
      ]
    },
    {
      "parameters": {
        "promptType": "define",
        "text": "={{ $json.prompt }}",
        "hasOutputParser": true,
        "options": {
          "systemMessage": "# IDENTIDADE\nVoc\u00ea \u00e9 o SENTINEL - Chief Intelligence Officer de IA da Mottivme.\n\n# MISS\u00c3O\nObservar silenciosamente opera\u00e7\u00f5es e identificar:\n- Processos (expl\u00edcitos e impl\u00edcitos)\n- Padr\u00f5es de decis\u00e3o\n- Gargalos operacionais\n- Oportunidades de automa\u00e7\u00e3o\n- Conhecimento t\u00e1cito\n\n# REGRAS CR\u00cdTICAS\n1. **S\u00d3 documente padr\u00f5es com 3+ evid\u00eancias** ou insights cr\u00edticos\n2. **SEMPRE cite exemplos concretos** das mensagens\n3. **QUANTIFIQUE** quando poss\u00edvel (\"7 de 10 casos\" n\u00e3o \"muitas vezes\")\n4. **SEJA ACION\u00c1VEL** - todo insight deve ter \"e da\u00ed?\"\n5. **NUNCA invente** - s\u00f3 documente o observado\n\n# TIPOS DE INSIGHT\n- `process_identified`: Novo processo mapeado\n- `decision_pattern`: Padr\u00e3o de decis\u00e3o identificado\n- `bottleneck_detected`: Gargalo operacional\n- `tacit_knowledge`: Conhecimento t\u00e1cito capturado\n- `automation_opportunity`: Chance de automatizar\n- `alert`: Problema cr\u00edtico que precisa aten\u00e7\u00e3o\n\n# FORMATO DE SA\u00cdDA\nRetorne um array de insights. Cada insight DEVE ter:\n- `insight_type`: Um dos tipos acima\n- `title`: T\u00edtulo descritivo (m\u00e1x 100 chars)\n- `content`: Descri\u00e7\u00e3o detalhada com evid\u00eancias\n- `confidence`: 0.0-1.0 (baseado em quantas evid\u00eancias)\n- `priority`: low/medium/high\n- `actionable_suggestion`: O que fazer com isso\n- `evidence_ids`: IDs das mensagens que geraram o insight\n\nSe n\u00e3o encontrar nada significativo, retorne array vazio."
        }
      },
      "type": "@n8n/n8n-nodes-langchain.agent",
      "typeVersion": 1.7,
      "position": [
        850,
        300
      ],
      "id": "ai-agent-sentinel",
      "name": "SENTINEL AI Agent"
    },
    {
      "parameters": {
        "model": "llama-3.3-70b-versatile",
        "options": {
          "temperature": 0.2,
          "maxTokens": 4000
        }
      },
      "type": "@n8n/n8n-nodes-langchain.lmChatGroq",
      "typeVersion": 1,
      "position": [
        850,
        520
      ],
      "id": "groq-model",
      "name": "Groq Chat Model",
      "credentials": {
        "groqApi": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {
        "jsonSchema": "{\n  \"type\": \"object\",\n  \"properties\": {\n    \"insights\": {\n      \"type\": \"array\",\n      \"items\": {\n        \"type\": \"object\",\n        \"properties\": {\n          \"insight_type\": {\n            \"type\": \"string\",\n            \"enum\": [\"process_identified\", \"decision_pattern\", \"bottleneck_detected\", \"tacit_knowledge\", \"automation_opportunity\", \"alert\"]\n          },\n          \"title\": {\n            \"type\": \"string\",\n            \"maxLength\": 100\n          },\n          \"content\": {\n            \"type\": \"string\"\n          },\n          \"confidence\": {\n            \"type\": \"number\",\n            \"minimum\": 0,\n            \"maximum\": 1\n          },\n          \"priority\": {\n            \"type\": \"string\",\n            \"enum\": [\"low\", \"medium\", \"high\"]\n          },\n          \"actionable_suggestion\": {\n            \"type\": \"string\"\n          },\n          \"evidence_ids\": {\n            \"type\": \"array\",\n            \"items\": {\n              \"type\": \"string\"\n            }\n          }\n        },\n        \"required\": [\"insight_type\", \"title\", \"content\", \"confidence\", \"priority\", \"actionable_suggestion\", \"evidence_ids\"]\n      }\n    }\n  },\n  \"required\": [\"insights\"]\n}"
      },
      "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
      "typeVersion": 1.2,
      "position": [
        1050,
        520
      ],
      "id": "output-parser",
      "name": "Structured Output Parser"
    },
    {
      "parameters": {
        "jsCode": "const aiOutput = $input.first().json;\nconst previousContext = $('Preparar Contexto para IA').first().json;\n\nlet insights = [];\n\n// Parse do output da IA\ntry {\n  if (aiOutput?.output?.insights) {\n    insights = aiOutput.output.insights;\n  } else if (aiOutput?.insights) {\n    insights = aiOutput.insights;\n  } else if (typeof aiOutput.output === 'string') {\n    const parsed = JSON.parse(aiOutput.output);\n    insights = parsed.insights || [];\n  }\n} catch (e) {\n  console.error('Erro ao parsear insights:', e);\n  return [];\n}\n\nif (!insights || insights.length === 0) {\n  console.log('Nenhum insight gerado pela IA');\n  return [];\n}\n\n// Prepara insights para inser\u00e7\u00e3o no banco\nreturn insights.map(insight => ({\n  json: {\n    insight_type: insight.insight_type,\n    title: insight.title,\n    content: insight.content,\n    confidence_score: insight.confidence,\n    metadata: {\n      priority: insight.priority,\n      actionable_suggestion: insight.actionable_suggestion,\n      evidence_ids: insight.evidence_ids,\n      total_messages_analyzed: previousContext.total_messages,\n      analysis_timestamp: new Date().toISOString()\n    },\n    processed_for_kb: false\n  }\n}));"
      },
      "id": "parse-insights",
      "name": "Parse e Prepara Insights",
      "type": "n8n-nodes-base.code",
      "typeVersion": 2,
      "position": [
        1050,
        300
      ]
    },
    {
      "parameters": {
        "operation": "executeQuery",
        "query": "INSERT INTO mottivme_intelligence_system.sentinel_insights (\n  insight_type,\n  content,\n  confidence_score,\n  metadata,\n  processed_for_kb\n) VALUES ($1, $2, $3, $4::jsonb, $5)\nRETURNING id, insight_type, confidence_score",
        "options": {
          "queryReplacement": "={{ [$json.insight_type, $json.title + '\\n\\n' + $json.content, $json.confidence_score, JSON.stringify($json.metadata), $json.processed_for_kb] }}"
        }
      },
      "id": "insert-insights",
      "name": "Salvar Insights",
      "type": "n8n-nodes-base.postgres",
      "typeVersion": 2.6,
      "position": [
        1250,
        300
      ],
      "credentials": {
        "postgres": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {
        "operation": "executeQuery",
        "query": "UPDATE mottivme_intelligence_system.messages\nSET processed_by_observer = true\nWHERE id = ANY($1::uuid[])\nRETURNING COUNT(*) as updated_count",
        "options": {
          "queryReplacement": "={{ ['{' + $('Preparar Contexto para IA').first().json.message_ids.join(',') + '}'] }}"
        }
      },
      "id": "mark-processed",
      "name": "Marcar Mensagens Processadas",
      "type": "n8n-nodes-base.postgres",
      "typeVersion": 2.6,
      "position": [
        1450,
        300
      ],
      "credentials": {
        "postgres": {
          "name": "<your credential>"
        }
      }
    }
  ],
  "connections": {
    "Schedule - Every 10min": {
      "main": [
        [
          {
            "node": "Buscar Mensagens N\u00e3o Processadas",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Buscar Mensagens N\u00e3o Processadas": {
      "main": [
        [
          {
            "node": "Preparar Contexto para IA",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Preparar Contexto para IA": {
      "main": [
        [
          {
            "node": "SENTINEL AI Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "SENTINEL AI Agent": {
      "main": [
        [
          {
            "node": "Parse e Prepara Insights",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Groq Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "SENTINEL AI Agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Structured Output Parser": {
      "ai_outputParser": [
        [
          {
            "node": "SENTINEL AI Agent",
            "type": "ai_outputParser",
            "index": 0
          }
        ]
      ]
    },
    "Parse e Prepara Insights": {
      "main": [
        [
          {
            "node": "Salvar Insights",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Salvar Insights": {
      "main": [
        [
          {
            "node": "Marcar Mensagens Processadas",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  },
  "settings": {
    "executionOrder": "v1"
  },
  "tags": [
    {
      "name": "SENTINEL"
    },
    {
      "name": "Intelligence"
    },
    {
      "name": "Observer"
    }
  ]
}

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.

• groqApi
• postgres

About this workflow

MIS - SENTINEL Intelligence Observer. Uses postgres, agent, lmChatGroq, outputParserStructured. Scheduled trigger; 9 nodes.

Source: https://github.com/marcosdanielsf/MIS-Sentinel/blob/f6ee8ebd9d2daf476120db9e365eba33a3407576/n8n-workflows/06-sentinel-intelligence-observer.json — original creator credit. Request a take-down →

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