Aula 4: Automação Inteligente Avançada

class AdaptiveFlowEngine {
  constructor() {
    this.observers = [];
    this.adaptationRules = [];
    this.performanceMetrics = new MetricsCollector();
    this.decisionEngine = new AIDecisionEngine();
  }

  // Observação contínua do fluxo
  observeFlow(flowId, metrics) {
    const currentPerformance = this.performanceMetrics.analyze(metrics);
    const patterns = this.detectPatterns(currentPerformance);
    
    if (this.shouldAdapt(patterns)) {
      this.triggerAdaptation(flowId, patterns);
    }
  }

  // Decisão inteligente de adaptação
  async triggerAdaptation(flowId, patterns) {
    const adaptationPlan = await this.decisionEngine.generatePlan({
      currentPatterns: patterns,
      historicalData: this.getHistoricalData(flowId),
      businessRules: this.getBusinessRules(flowId)
    });

    // Validação e aplicação segura
    if (this.validateAdaptation(adaptationPlan)) {
      await this.applyAdaptation(flowId, adaptationPlan);
      this.monitorAdaptationResults(flowId, adaptationPlan);
    }
  }

  // Aplicação segura com rollback
  async applyAdaptation(flowId, plan) {
    const checkpoint = this.createCheckpoint(flowId);
    
    try {
      await this.executeAdaptationPlan(plan);
      await this.validateNewBehavior(flowId);
    } catch (error) {
      await this.rollbackToCheckpoint(flowId, checkpoint);
      this.logAdaptationFailure(error, plan);
    }
  }
}

class AdaptiveRulesEngine {
  constructor() {
    this.rules = new Map();
    this.rulePerformance = new Map();
    this.geneticOptimizer = new GeneticAlgorithmOptimizer();
  }

  // Define regra adaptativa
  defineRule(ruleId, config) {
    const rule = {
      id: ruleId,
      condition: config.condition,      // Quando aplicar
      action: config.action,           // O que fazer
      parameters: config.parameters,   // Parâmetros ajustáveis
      performance: {
        successRate: 0,
        avgImpact: 0,
        executionCount: 0
      }
    };

    this.rules.set(ruleId, rule);
  }

  // Evolução automática de regras
  async evolveRules() {
    const performanceData = this.collectRulePerformance();
    
    // Identifica regras de baixa performance
    const underperformingRules = this.identifyUnderperformers(performanceData);
    
    // Gera variações usando algoritmo genético
    const newVariations = await this.geneticOptimizer.generateVariations(
      underperformingRules
    );

    // Testa variações em ambiente controlado
    const testResults = await this.testVariations(newVariations);
    
    // Aplica melhores variações
    this.applyBestVariations(testResults);
  }

  // Execução adaptativa de regras
  async executeAdaptiveRule(ruleId, context) {
    const rule = this.rules.get(ruleId);
    
    // Ajusta parâmetros baseado em performance histórica
    const optimizedParameters = this.optimizeParameters(rule, context);
    
    // Executa com parâmetros otimizados
    const result = await this.executeRule(rule, optimizedParameters, context);
    
    // Coleta feedback para evolução futura
    this.recordRuleExecution(ruleId, result, context);
    
    return result;
  }
}

// Sistema completo de fluxos adaptativos
class CompleteAdaptiveFlowSystem {
  constructor() {
    this.flowEngine = new AdaptiveFlowEngine();
    this.rulesEngine = new AdaptiveRulesEngine();
    this.metricsCollector = new RealTimeMetricsCollector();
    this.adaptationHistory = new AdaptationHistoryTracker();
  }

  // Inicialização do sistema adaptativo
  async initialize() {
    // Configura regras base
    await this.setupBaseRules();
    
    // Inicia monitoramento contínuo
    this.startContinuousMonitoring();
    
    // Ativa evolução automática
    this.enableAutoEvolution();
  }

  // Configuração de regras adaptativas base
  async setupBaseRules() {
    // Regra de adaptação por tempo de resposta
    this.rulesEngine.defineRule('RESPONSE_TIME_OPTIMIZATION', {
      condition: (metrics) => metrics.avgResponseTime > 3000,
      action: 'SCALE_AGENT_POOL',
      parameters: {
        scaleStrategy: 'SMART_SCALING',
        maxAgents: 50,
        cooldownPeriod: 300
      }
    });

    // Regra de adaptação por satisfação
    this.rulesEngine.defineRule('SATISFACTION_IMPROVEMENT', {
      condition: (metrics) => metrics.satisfactionScore < 4.0,
      action: 'ENHANCE_RESPONSE_QUALITY',
      parameters: {
        qualityBoost: 0.2,
        expertRoutingThreshold: 0.8,
        proactiveMode: true
      }
    });

    // Regra de adaptação comportamental
    this.rulesEngine.defineRule('BEHAVIORAL_ADAPTATION', {
      condition: (context) => context.behavioralShift > 0.6,
      action: 'ADAPT_COMMUNICATION_STYLE',
      parameters: {
        adaptationSpeed: 'GRADUAL',
        rollbackThreshold: 0.3,
        testDuration: 3600
      }
    });
  }

  // Processamento de mensagem com adaptação
  async processMessage(message, userId) {
    const context = await this.buildContext(message, userId);
    
    // Coleta métricas em tempo real
    const currentMetrics = this.metricsCollector.getCurrentMetrics();
    
    // Aplica adaptações necessárias
    const adaptations = await this.determineAdaptations(context, currentMetrics);
    
    // Executa processamento adaptativo
    const result = await this.executeAdaptiveProcessing(
      message, 
      context, 
      adaptations
    );

    // Registra resultado para aprendizado
    this.recordAdaptationResult(adaptations, result);
    
    return result;
  }

  // Sistema de evolução contínua
  startAutoEvolution() {
    setInterval(async () => {
      // Analisa performance dos últimos ciclos
      const performanceReport = await this.generatePerformanceReport();
      
      // Identifica oportunidades de melhoria
      const improvements = this.identifyImprovementOpportunities(performanceReport);
      
      // Implementa melhorias de forma segura
      await this.implementImprovements(improvements);
      
    }, 3600000); // Evolução a cada hora
  }
}

class ProactiveAutomationEngine {
  constructor() {
    this.predictiveModels = new PredictiveModelRepository();
    this.actionRegistry = new ProactiveActionRegistry();
    this.contextAnalyzer = new DeepContextAnalyzer();
    this.riskCalculator = new RiskAssessmentEngine();
  }

  // Análise proativa contínua
  async analyzeUserContext(userId, currentSession) {
    const context = await this.contextAnalyzer.buildComprehensiveContext({
      userId,
      currentSession,
      historicalData: await this.getUserHistory(userId),
      behavioralPatterns: await this.getBehavioralPatterns(userId),
      externalFactors: await this.getExternalFactors()
    });

    // Gera predições baseadas no contexto
    const predictions = await this.generatePredictions(context);
    
    // Avalia oportunidades proativas
    const opportunities = this.evaluateProactiveOpportunities(predictions);
    
    // Executa ações com maior probabilidade de sucesso
    await this.executeProactiveActions(opportunities);
  }

  // Geração de predições inteligentes
  async generatePredictions(context) {
    const models = await this.predictiveModels.getActiveModels();
    const predictions = [];

    for (const model of models) {
      const prediction = await model.predict(context);
      
      if (prediction.confidence > 0.75) {
        predictions.push({
          type: prediction.type,
          probability: prediction.confidence,
          timeframe: prediction.expectedTimeframe,
          impact: this.calculatePotentialImpact(prediction),
          suggestedActions: await this.getSuggestedActions(prediction)
        });
      }
    }

    return this.prioritizePredictions(predictions);
  }

  // Execução inteligente de ações proativas
  async executeProactiveActions(opportunities) {
    for (const opportunity of opportunities) {
      const riskAssessment = await this.riskCalculator.assess(opportunity);
      
      if (riskAssessment.isAcceptable) {
        const action = await this.actionRegistry.getAction(opportunity.type);
        
        // Executa com monitoramento de resultado
        const result = await this.executeWithMonitoring(action, opportunity);
        
        // Aprende com o resultado para futuras predições
        await this.learnFromResult(opportunity, result);
      }
    }
  }
}

class IntelligentTriggerSystem {
  constructor() {
    this.triggerEngine = new AdvancedTriggerEngine();
    this.contextProcessor = new ContextProcessor();
    this.actionExecutor = new ActionExecutor();
    this.learningEngine = new ContinuousLearningEngine();
  }

  // Configuração de triggers adaptativos
  setupAdaptiveTriggers() {
    // Trigger baseado em comportamento
    this.triggerEngine.defineTrigger('BEHAVIOR_CHANGE', {
      condition: (context) => {
        const behaviorShift = this.detectBehaviorShift(context);
        return behaviorShift.magnitude > 0.6 && behaviorShift.direction === 'POSITIVE';
      },
      action: 'PROACTIVE_ENGAGEMENT',
      adaptiveParameters: {
        sensitivity: 'AUTO_ADJUST',
        cooldown: 'DYNAMIC',
        personalization: 'HIGH'
      }
    });

    // Trigger baseado em momento ótimo
    this.triggerEngine.defineTrigger('OPTIMAL_MOMENT', {
      condition: (context) => {
        const engagement = this.calculateEngagementScore(context);
        const availability = this.assessAvailability(context);
        const mood = this.detectMood(context);
        
        return engagement > 0.8 && availability > 0.7 && mood === 'POSITIVE';
      },
      action: 'PERSONALIZED_OFFER',
      adaptiveParameters: {
        timing: 'REAL_TIME_OPTIMIZATION',
        content: 'DYNAMIC_PERSONALIZATION',
        frequency: 'SMART_LIMITING'
      }
    });

    // Trigger baseado em necessidade latente
    this.triggerEngine.defineTrigger('LATENT_NEED', {
      condition: (context) => {
        const needs = this.identifyLatentNeeds(context);
        const satisfaction = this.assessCurrentSatisfaction(context);
        
        return needs.length > 0 && satisfaction < 0.6;
      },
      action: 'PROACTIVE_SOLUTION',
      adaptiveParameters: {
        prediction_confidence: 'MINIMUM_75_PERCENT',
        solution_relevance: 'HIGH',
        user_receptivity: 'OPTIMIZED'
      }
    });
  }

  // Processamento em tempo real
  async processRealTimeContext(userId, contextData) {
    const enrichedContext = await this.contextProcessor.enrich({
      userId,
      currentData: contextData,
      historical: await this.getHistoricalContext(userId),
      external: await this.getExternalContext(userId)
    });

    // Avalia todos os triggers configurados
    const activatedTriggers = await this.triggerEngine.evaluate(enrichedContext);
    
    // Executa ações priorizadas
    for (const trigger of activatedTriggers) {
      if (await this.shouldExecute(trigger, enrichedContext)) {
        const result = await this.actionExecutor.execute(trigger, enrichedContext);
        
        // Aprende com o resultado
        await this.learningEngine.recordExecution(trigger, result, enrichedContext);
      }
    }
  }

  // Otimização contínua de triggers
  async optimizeTriggers() {
    const performance = await this.learningEngine.analyzePerformance();
    
    // Identifica triggers de baixa performance
    const underperformers = performance.filter(t => t.successRate < 0.6);
    
    // Otimiza parâmetros automaticamente
    for (const trigger of underperformers) {
      const optimizations = await this.learningEngine.suggestOptimizations(trigger);
      await this.triggerEngine.updateTrigger(trigger.id, optimizations);
    }
  }
}

// Sistema completo de automação inteligente avançada
class AdvancedAutomationSystem {
  constructor() {
    // Núcleo do sistema
    this.orchestrator = new MultiAgentOrchestrator();
    this.adaptiveEngine = new AdaptiveFlowEngine();
    this.proactiveSystem = new ProactiveAutomationEngine();
    this.intelligence = new OperationalIntelligenceCore();
    
    // Infraestrutura de suporte
    this.dataProcessor = new RealTimeDataProcessor();
    this.messageRouter = new IntelligentMessageRouter();
    this.sessionManager = new AdvancedSessionManager();
    this.analytics = new ComprehensiveAnalyticsEngine();
  }

  // Inicialização completa do sistema
  async initialize() {
    console.log('🚀 Inicializando Sistema de Automação Avançada...');
    
    // Inicializa componentes em ordem de dependência
    await this.dataProcessor.initialize();
    await this.intelligence.initialize();
    await this.orchestrator.initialize();
    await this.adaptiveEngine.initialize();
    await this.proactiveSystem.initialize();
    
    // Configura interconexões
    await this.setupInterconnections();
    
    // Ativa monitoramento contínuo
    this.startContinuousMonitoring();
    
    console.log('✅ Sistema completamente inicializado!');
  }

  // Configuração de interconexões entre componentes
  async setupInterconnections() {
    // Inteligência Operacional alimenta todos os outros sistemas
    this.intelligence.onInsight((insight) => {
      this.orchestrator.processInsight(insight);
      this.adaptiveEngine.adaptBasedOnInsight(insight);
      this.proactiveSystem.evaluateProactiveAction(insight);
    });

    // Fluxos adaptativos informam orquestrador
    this.adaptiveEngine.onAdaptation((adaptation) => {
      this.orchestrator.updateStrategy(adaptation);
      this.intelligence.recordAdaptation(adaptation);
    });

    // Sistema proativo coordena com orquestrador
    this.proactiveSystem.onProactiveAction((action) => {
      this.orchestrator.allocateResourcesForAction(action);
      this.intelligence.trackProactiveImpact(action);
    });
  }

  // Processamento principal de mensagens
  async processMessage(phoneNumber, message, context = {}) {
    console.log(`📨 Processando mensagem de ${phoneNumber}`);
    
    try {
      // 1. Análise contextual profunda
      const enrichedContext = await this.buildEnrichedContext(
        phoneNumber, 
        message, 
        context
      );

      // 2. Roteamento inteligente
      const routingDecision = await this.messageRouter.route(
        message, 
        enrichedContext
      );

      // 3. Processamento multi-agente
      const agentResponse = await this.orchestrator.processWithAgents(
        message,
        enrichedContext,
        routingDecision
      );

      // 4. Adaptação em tempo real
      await this.adaptiveEngine.adaptBasedOnInteraction(
        enrichedContext,
        agentResponse
      );

      // 5. Avaliação de ações proativas
      await this.proactiveSystem.evaluatePostInteraction(
        enrichedContext,
        agentResponse
      );

      // 6. Coleta de inteligência operacional
      await this.intelligence.processInteractionData({
        context: enrichedContext,
        response: agentResponse,
        outcome: 'SUCCESS'
      });

      return agentResponse;

    } catch (error) {
      console.error('❌ Erro no processamento:', error);
      
      // Sistema de recuperação inteligente
      return await this.handleProcessingError(phoneNumber, message, error);
    }
  }
}

class UnifiedContextSystem {
  constructor() {
    this.userProfileManager = new AdvancedUserProfileManager();
    this.conversationMemory = new ConversationMemoryEngine();
    this.behaviorAnalyzer = new BehaviorAnalysisEngine();
    this.externalContext = new ExternalContextProvider();
  }

  // Construção de contexto ultra-rico
  async buildEnrichedContext(phoneNumber, message, baseContext) {
    const startTime = Date.now();
    
    // Coleta dados em paralelo para máxima velocidade
    const [
      userProfile,
      conversationHistory,
      behaviorProfile,
      externalData,
      systemMetrics
    ] = await Promise.all([
      this.userProfileManager.getProfile(phoneNumber),
      this.conversationMemory.getHistory(phoneNumber, 50),
      this.behaviorAnalyzer.analyzeBehavior(phoneNumber),
      this.externalContext.getContextualData(phoneNumber),
      this.getSystemMetrics()
    ]);

    // Análise semântica da mensagem atual
    const messageAnalysis = await this.analyzeMessage(message, userProfile);
    
    // Detecção de intenção avançada
    const intentAnalysis = await this.detectIntent(
      message, 
      conversationHistory, 
      behaviorProfile
    );

    // Análise de sentimento contextual
    const sentimentAnalysis = await this.analyzeSentiment(
      message, 
      userProfile, 
      conversationHistory
    );

    const enrichedContext = {
      // Dados básicos
      phoneNumber,
      message,
      timestamp: new Date(),
      
      // Perfil do usuário
      userProfile: {
        ...userProfile,
        currentMood: sentimentAnalysis.mood,
        engagementLevel: behaviorProfile.currentEngagement,
        preferredCommunicationStyle: userProfile.communicationPreferences
      },

      // Contexto conversacional
      conversation: {
        history: conversationHistory,
        currentTopic: intentAnalysis.topic,
        conversationStage: this.determineConversationStage(conversationHistory),
        urgencyLevel: intentAnalysis.urgency
      },

      // Análise comportamental
      behavior: {
        patterns: behaviorProfile.patterns,
        preferences: behaviorProfile.preferences,
        predictedNeeds: behaviorProfile.predictedNeeds,
        riskFactors: behaviorProfile.riskFactors
      },

      // Contexto externo
      external: {
        timeOfDay: new Date().getHours(),
        dayOfWeek: new Date().getDay(),
        businessHours: externalData.businessHours,
        systemLoad: systemMetrics.currentLoad,
        marketConditions: externalData.marketData
      },

      // Análise da mensagem
      messageAnalysis: {
        intent: intentAnalysis.intent,
        confidence: intentAnalysis.confidence,
        entities: messageAnalysis.entities,
        sentiment: sentimentAnalysis.sentiment,
        complexity: messageAnalysis.complexity,
        urgency: intentAnalysis.urgency
      },

      // Meta informações
      meta: {
        contextBuildTime: Date.now() - startTime,
        dataQuality: this.assessDataQuality(userProfile, conversationHistory),
        confidence: this.calculateOverallConfidence(intentAnalysis, sentimentAnalysis)
      }
    };

    // Enriquece com insights de IA
    return await this.enrichWithAIInsights(enrichedContext);
  }

  // Análise de intenção multi-camadas
  async detectIntent(message, history, behaviorProfile) {
    const models = [
      this.primaryIntentModel,
      this.contextualIntentModel,
      this.behavioralIntentModel
    ];

    const predictions = await Promise.all(
      models.map(model => model.predict({
        message,
        history: history.slice(-10),
        behavior: behaviorProfile
      }))
    );

    // Fusão inteligente de predições
    const fusedPrediction = this.fuseIntentPredictions(predictions);
    
    return {
      intent: fusedPrediction.intent,
      confidence: fusedPrediction.confidence,
      topic: fusedPrediction.topic,
      urgency: this.calculateUrgency(fusedPrediction, behaviorProfile),
      subIntents: fusedPrediction.subIntents
    };
  }
}

class IntelligentResponseEngine {
  constructor() {
    this.responseGenerator = new AdvancedResponseGenerator();
    this.personalizer = new ResponsePersonalizer();
    this.qualityAssurance = new ResponseQualityAssurance();
    this.deliveryOptimizer = new DeliveryOptimizer();
  }

  // Geração de resposta multi-estratégia
  async generateResponse(context, agentDecision) {
    const strategies = await this.selectResponseStrategies(context, agentDecision);
    
    const candidateResponses = await Promise.all(
      strategies.map(strategy => this.generateResponseWithStrategy(
        context, 
        agentDecision, 
        strategy
      ))
    );

    // Avalia qualidade de cada candidata
    const evaluatedResponses = await Promise.all(
      candidateResponses.map(response => this.evaluateResponse(response, context))
    );

    // Seleciona melhor resposta
    const bestResponse = this.selectBestResponse(evaluatedResponses);
    
    // Personaliza para o usuário específico
    const personalizedResponse = await this.personalizer.personalize(
      bestResponse, 
      context
    );

    // Otimiza entrega
    const optimizedResponse = await this.deliveryOptimizer.optimize(
      personalizedResponse,
      context
    );

    return optimizedResponse;
  }

  // Seleção de estratégias de resposta
  async selectResponseStrategies(context, agentDecision) {
    const strategies = [];

    // Estratégia baseada no tipo de intenção
    if (context.messageAnalysis.intent === 'SUPPORT') {
      strategies.push('EMPATHETIC_SUPPORT');
      strategies.push('SOLUTION_FOCUSED');
    } else if (context.messageAnalysis.intent === 'SALES') {
      strategies.push('CONSULTATIVE_SELLING');
      strategies.push('VALUE_PROPOSITION');
    }

    // Estratégia baseada no humor do usuário
    if (context.userProfile.currentMood === 'FRUSTRATED') {
      strategies.push('CALMING_RESOLUTION');
    } else if (context.userProfile.currentMood === 'EXCITED') {
      strategies.push('ENTHUSIASM_MATCHING');
    }

    // Estratégia baseada na urgência
    if (context.messageAnalysis.urgency === 'HIGH') {
      strategies.push('IMMEDIATE_ACTION');
    }

    return this.optimizeStrategyMix(strategies, context);
  }

  // Avaliação de qualidade da resposta
  async evaluateResponse(response, context) {
    const metrics = {
      relevance: await this.assessRelevance(response, context),
      clarity: await this.assessClarity(response),
      empathy: await this.assessEmpathy(response, context),
      actionability: await this.assessActionability(response),
      personalization: await this.assessPersonalization(response, context),
      brandAlignment: await this.assessBrandAlignment(response)
    };

    const overallScore = this.calculateOverallScore(metrics);
    
    return {
      response,
      metrics,
      score: overallScore,
      improvements: await this.suggestImprovements(response, metrics)
    };
  }

  // Personalização avançada
  async personalizeResponse(response, context) {
    const personalizations = {
      // Ajusta tom baseado no perfil
      tone: await this.adjustTone(response, context.userProfile),
      
      // Adapta complexidade baseado no histórico
      complexity: await this.adjustComplexity(response, context.behavior),
      
      // Adiciona elementos pessoais
      personal: await this.addPersonalElements(response, context.userProfile),
      
      // Otimiza timing de entrega
      timing: await this.optimizeDeliveryTiming(response, context),
      
      // Seleciona formato ideal
      format: await this.selectOptimalFormat(response, context.userProfile)
    };

    return this.applyPersonalizations(response, personalizations);
  }

  // Sistema de melhoria contínua
  async learnFromResponse(response, context, outcome) {
    const learningData = {
      context: this.extractLearningContext(context),
      response: response,
      outcome: outcome,
      userFeedback: outcome.userFeedback,
      effectivenessMetrics: outcome.metrics
    };

    // Atualiza modelos de geração
    await this.responseGenerator.updateModels(learningData);
    
    // Melhora personalização
    await this.personalizer.improvePerson personalization(learningData);
    
    // Refina avaliação de qualidade
    await this.qualityAssurance.refineAssessment(learningData);
  }
}

class MonitoringOptimizationSystem {
  constructor() {
    this.metricsCollector = new ComprehensiveMetricsCollector();
    this.performanceAnalyzer = new PerformanceAnalyzer();
    this.optimizationEngine = new ContinuousOptimizationEngine();
    this.alertManager = new IntelligentAlertManager();
  }

  // Monitoramento em tempo real
  startRealTimeMonitoring() {
    // Coleta métricas a cada segundo
    setInterval(async () => {
      const metrics = await this.collectRealTimeMetrics();
      await this.processMetrics(metrics);
    }, 1000);

    // Análise profunda a cada minuto
    setInterval(async () => {
      await this.performDeepAnalysis();
    }, 60000);

    // Otimização automática a cada hora
    setInterval(async () => {
      await this.performOptimization();
    }, 3600000);
  }

  // Coleta abrangente de métricas
  async collectRealTimeMetrics() {
    return {
      // Métricas de performance
      performance: {
        responseTime: await this.measureResponseTime(),
        throughput: await this.measureThroughput(),
        errorRate: await this.calculateErrorRate(),
        resourceUtilization: await this.getResourceUtilization()
      },

      // Métricas de qualidade
      quality: {
        userSatisfaction: await this.getCurrentSatisfaction(),
        resolutionRate: await this.getResolutionRate(),
        escalationRate: await this.getEscalationRate(),
        repeatContactRate: await this.getRepeatContactRate()
      },

      // Métricas de negócio
      business: {
        conversionRate: await this.getConversionRate(),
        revenuePerInteraction: await this.getRevenuePerInteraction(),
        customerLifetimeValue: await this.getCLV(),
        churnRate: await this.getChurnRate()
      },

      // Métricas de agentes
      agents: {
        agentUtilization: await this.getAgentUtilization(),
        agentPerformance: await this.getAgentPerformance(),
        agentAccuracy: await this.getAgentAccuracy(),
        agentLearningRate: await this.getAgentLearningRate()
      }
    };
  }

  // Análise de performance e identificação de gargalos
  async performDeepAnalysis() {
    const metrics = await this.collectRealTimeMetrics();
    const analysis = await this.performanceAnalyzer.analyze(metrics);
    
    // Identifica gargalos
    const bottlenecks = analysis.bottlenecks.filter(b => b.impact > 0.1);
    
    // Identifica oportunidades
    const opportunities = analysis.opportunities.filter(o => o.potential > 0.15);
    
    // Gera alertas se necessário
    if (bottlenecks.length > 0) {
      await this.alertManager.sendBottleneckAlert(bottlenecks);
    }
    
    // Agenda otimizações
    if (opportunities.length > 0) {
      await this.scheduleOptimizations(opportunities);
    }

    return { bottlenecks, opportunities, analysis };
  }

  // Sistema de otimização contínua
  async performOptimization() {
    const currentPerformance = await this.getCurrentPerformance();
    const optimizationTargets = await this.identifyOptimizationTargets();
    
    for (const target of optimizationTargets) {
      const optimization = await this.optimizationEngine.optimize(target);
      
      // Testa otimização em ambiente controlado
      const testResult = await this.testOptimization(optimization);
      
      if (testResult.improvement > 0.05) {
        // Implementa otimização gradualmente
        await this.implementOptimization(optimization);
        
        // Monitora resultados
        await this.monitorOptimizationResults(optimization);
      }
    }
  }

  // Dashboard executivo em tempo real
  async generateExecutiveDashboard() {
    const metrics = await this.collectRealTimeMetrics();
    const analysis = await this.performDeepAnalysis();
    
    return {
      summary: {
        overallHealth: this.calculateOverallHealth(metrics),
        keyMetrics: this.extractKeyMetrics(metrics),
        trends: this.identifyTrends(metrics),
        alerts: this.getActiveAlerts()
      },
      
      performance: {
        current: metrics.performance,
        targets: await this.getPerformanceTargets(),
        benchmarks: await this.getBenchmarks(),
        improvements: analysis.opportunities
      },
      
      business: {
        current: metrics.business,
        forecast: await this.generateForecast(metrics.business),
        opportunities: analysis.opportunities.filter(o => o.type === 'BUSINESS'),
        risks: analysis.bottlenecks.filter(b => b.businessImpact > 0.1)
      },
      
      recommendations: await this.generateExecutiveRecommendations(metrics, analysis)
    };
  }
}