From 1646c420397fd638308a78b024586aba85a2d51e Mon Sep 17 00:00:00 2001 From: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Mon, 11 Aug 2025 01:08:14 +0000 Subject: [PATCH] Add TypeScript workflow functions to RideResolve MDX - Added comprehensive business process workflows as executable TypeScript code - Includes customer acquisition, product development, revenue generation flows - Added operational procedures for ticket processing and safety escalation - Implemented decision-making workflows for routing and automation optimization - All functions include proper typing, async/await patterns, and error handling - Functions represent core RideResolve business logic for rideshare support automation Co-Authored-By: unknown <> --- startups/rideresolve.mdx | 404 +++++++++++++++++++++++++++++++++++++++ 1 file changed, 404 insertions(+) diff --git a/startups/rideresolve.mdx b/startups/rideresolve.mdx index a5be5b1..04868bc 100644 --- a/startups/rideresolve.mdx +++ b/startups/rideresolve.mdx @@ -307,7 +307,411 @@ landingPage: - Train on historical tickets; launch a monitored pilot. - Scale to 24/7 coverage with dashboards and continuous learning. --- + # RideResolve AI Generated for NAICS 485310 — Taxi and Ridesharing Services. Service: Customer Support Auto‑Triage and Responder + +## Business Process Workflows + +The following TypeScript functions represent RideResolve's core business processes as executable code: + +```typescript +// Types and Interfaces +interface Lead { + id: string; + company: string; + contactInfo: ContactInfo; + fleetSize: number; + currentSupportVolume: number; + painPoints: string[]; + budget: number; + timeline: string; +} + +interface Customer { + id: string; + company: string; + contractValue: number; + integrations: Integration[]; + supportMetrics: SupportMetrics; + onboardingStatus: OnboardingStatus; +} + +interface SupportTicket { + id: string; + customerId: string; + rideId?: string; + channel: 'chat' | 'email' | 'sms' | 'voice' | 'app'; + content: string; + metadata: TicketMetadata; + priority: 'low' | 'medium' | 'high' | 'critical'; + intent?: string; + sentiment?: number; +} + +interface PolicyDecision { + action: 'approve' | 'deny' | 'escalate'; + amount?: number; + reasoning: string; + confidence: number; + auditTrail: AuditEntry[]; +} + +interface SafetyEscalation { + ticketId: string; + riskLevel: 'medium' | 'high' | 'critical'; + keywords: string[]; + escalatedAt: Date; + assignedAgent?: string; + responseTime: number; +} + +// Customer Acquisition Workflows +export async function acquireCustomer(lead: Lead): Promise { + const qualifiedLead = await qualifyLead(lead); + const demo = await scheduleDemoCall(qualifiedLead); + const pilot = await proposePilotProgram(demo); + const contract = await negotiateContract(pilot); + return await onboardCustomer(contract); +} + +export async function qualifyLead(lead: Lead): Promise { + // Validate fleet size and support volume thresholds + if (lead.fleetSize < 50 || lead.currentSupportVolume < 1000) { + throw new Error('Lead does not meet minimum qualification criteria'); + } + + const fitScore = await calculateFitScore(lead); + const roiEstimate = await generateROIEstimate(lead); + + return { + ...lead, + fitScore, + roiEstimate, + qualifiedAt: new Date(), + nextAction: fitScore > 70 ? 'schedule_demo' : 'nurture_sequence' + }; +} + +export async function conductPilotProgram(customer: Customer): Promise { + const pilotConfig = await setupPilotEnvironment(customer); + const trainingData = await collectHistoricalTickets(customer, 90); // 90 days + + const aiModel = await trainCustomerModel(trainingData); + const pilotMetrics = await runPilotPhase(aiModel, pilotConfig, 30); // 30 day pilot + + return { + automationRate: pilotMetrics.automationRate, + csatImprovement: pilotMetrics.csatDelta, + costSavings: pilotMetrics.costReduction, + safetyAccuracy: pilotMetrics.safetyEscalationAccuracy, + recommendation: pilotMetrics.automationRate > 0.3 ? 'proceed_to_full' : 'extend_pilot' + }; +} + +// Product Development Processes +export async function developAIModel(customerData: CustomerData): Promise { + const labeledDataset = await createLabeledDataset(customerData); + const baseModel = await loadPretrainedModel('rideshare-support-v2'); + + const customModel = await fineTuneModel(baseModel, labeledDataset); + const validationResults = await validateModel(customModel); + + if (validationResults.accuracy < 0.94) { + throw new Error('Model accuracy below threshold, requires additional training'); + } + + return await deployModel(customModel); +} + +export async function integrateWithPlatform(customer: Customer, platform: SupportPlatform): Promise { + const apiCredentials = await validatePlatformAccess(platform); + const webhookEndpoints = await setupWebhooks(platform, customer); + + const integration = await createIntegration({ + customerId: customer.id, + platform: platform.type, + endpoints: webhookEndpoints, + credentials: apiCredentials + }); + + await testIntegration(integration); + return integration; +} + +export async function updatePolicyEngine(policies: PolicyRule[]): Promise { + const validatedPolicies = await validatePolicyRules(policies); + const testResults = await simulatePolicyChanges(validatedPolicies); + + if (testResults.leakageRisk > 0.005) { // 0.5% threshold + throw new Error('Policy changes exceed acceptable leakage risk'); + } + + return await deployPolicyUpdate(validatedPolicies); +} + +// Revenue Generation Flows +export async function processUsageBasedBilling(customer: Customer, month: string): Promise { + const usageMetrics = await collectUsageMetrics(customer.id, month); + const pricingTier = await determinePricingTier(usageMetrics.volume); + + const lineItems = [ + { + description: 'Automated Resolutions', + quantity: usageMetrics.automatedResolutions, + unitPrice: pricingTier.automationPrice, + amount: usageMetrics.automatedResolutions * pricingTier.automationPrice + }, + { + description: 'Triage Operations', + quantity: usageMetrics.triageOperations, + unitPrice: pricingTier.triagePrice, + amount: usageMetrics.triageOperations * pricingTier.triagePrice + } + ]; + + const invoice = await generateInvoice(customer, lineItems, month); + await sendInvoice(invoice); + + return invoice; +} + +export async function manageSubscription(customer: Customer, action: SubscriptionAction): Promise { + switch (action.type) { + case 'upgrade': + return await upgradeSubscription(customer, action.newTier); + case 'downgrade': + return await downgradeSubscription(customer, action.newTier); + case 'cancel': + return await cancelSubscription(customer, action.effectiveDate); + case 'renew': + return await renewSubscription(customer, action.terms); + default: + throw new Error(`Unknown subscription action: ${action.type}`); + } +} + +// Operational Procedures +export async function processTicket(ticket: SupportTicket): Promise { + try { + // Step 1: Classify intent and extract metadata + const classification = await classifyTicket(ticket); + const rideContext = await fetchRideContext(ticket.rideId); + + // Step 2: Safety check - highest priority + const safetyCheck = await detectSafetyIssues(ticket, classification); + if (safetyCheck.requiresEscalation) { + return await escalateToSafety(ticket, safetyCheck); + } + + // Step 3: Attempt automated resolution + if (classification.confidence > 0.85 && classification.intent in AUTOMATABLE_INTENTS) { + const resolution = await attemptAutomatedResolution(ticket, classification, rideContext); + if (resolution.success) { + await sendAutomatedResponse(ticket, resolution); + return resolution; + } + } + + // Step 4: Generate agent assist + const agentAssist = await generateAgentAssist(ticket, classification, rideContext); + return await escalateToAgent(ticket, agentAssist); + + } catch (error) { + await logError(error, ticket); + return await escalateToAgent(ticket, { error: error.message }); + } +} + +export async function handleSafetyEscalation(ticket: SupportTicket, safetySignals: SafetySignals): Promise { + const escalation: SafetyEscalation = { + ticketId: ticket.id, + riskLevel: safetySignals.riskLevel, + keywords: safetySignals.detectedKeywords, + escalatedAt: new Date(), + responseTime: 0 + }; + + // Immediate actions for safety escalation + await pauseAutomation(ticket.customerId); + await triggerSafetyAlert(escalation); + await notifyOnCallTeam(escalation); + + // Assign to next available safety specialist + const agent = await assignSafetySpecialist(escalation); + escalation.assignedAgent = agent.id; + escalation.responseTime = Date.now() - escalation.escalatedAt.getTime(); + + // Ensure <30 second SLA + if (escalation.responseTime > 30000) { + await triggerSLABreach(escalation); + } + + await logSafetyEscalation(escalation); + return escalation; +} + +export async function enforcePolicy(ticket: SupportTicket, policyType: PolicyType): Promise { + const policyEngine = await loadPolicyEngine(ticket.customerId); + const rideData = await fetchRideData(ticket.rideId); + const customerHistory = await getCustomerHistory(ticket.customerId); + + const decision = await policyEngine.evaluate({ + ticket, + rideData, + customerHistory, + policyType + }); + + // Audit trail for compliance + const auditEntry: AuditEntry = { + timestamp: new Date(), + action: decision.action, + reasoning: decision.reasoning, + confidence: decision.confidence, + reviewedBy: decision.confidence < 0.95 ? 'human_required' : 'automated' + }; + + await logPolicyDecision(decision, auditEntry); + + if (decision.confidence < 0.95) { + return await escalateForPolicyReview(ticket, decision); + } + + return decision; +} + +// Decision-Making Workflows +export async function routeTicket(ticket: SupportTicket): Promise { + const classification = await classifyTicket(ticket); + const customerConfig = await getCustomerConfiguration(ticket.customerId); + + // Priority routing logic + if (classification.safety.risk > 0.7) { + return { + destination: 'safety_team', + priority: 'critical', + sla: 30, // seconds + reasoning: 'Safety risk detected' + }; + } + + if (classification.intent in customerConfig.automatedIntents && classification.confidence > 0.85) { + return { + destination: 'automation_engine', + priority: 'normal', + sla: 60, // seconds + reasoning: 'High confidence automated resolution available' + }; + } + + // Route to appropriate human queue + const queueAssignment = await determineQueue(classification, customerConfig); + return { + destination: queueAssignment.queue, + priority: queueAssignment.priority, + sla: queueAssignment.sla, + reasoning: queueAssignment.reasoning + }; +} + +export async function optimizeAutomationRules(customer: Customer): Promise { + const performanceData = await collectAutomationMetrics(customer.id, 30); // 30 days + const currentConfig = await getCurrentAutomationConfig(customer.id); + + // Analyze performance by intent + const intentAnalysis = await analyzeIntentPerformance(performanceData); + const optimizedRules = await generateOptimizedRules(intentAnalysis, currentConfig); + + // A/B test new rules + const testResults = await runAutomationTest(optimizedRules, customer.id, 7); // 7 day test + + if (testResults.improvement > 0.05) { // 5% improvement threshold + await deployAutomationConfig(optimizedRules, customer.id); + return optimizedRules; + } + + return currentConfig; // Keep existing if no significant improvement +} + +export async function generateInsights(customer: Customer, timeframe: string): Promise { + const metrics = await collectMetrics(customer.id, timeframe); + const trends = await analyzeTrends(metrics); + const benchmarks = await getBenchmarkData(customer.industry); + + return { + automationRate: metrics.automationRate, + csatTrend: trends.csat, + costSavings: calculateCostSavings(metrics, customer.baseline), + recommendations: await generateRecommendations(trends, benchmarks), + alerts: await detectAnomalies(metrics, customer.thresholds) + }; +} + +// Multilingual Support Workflow +export async function handleMultilingualTicket(ticket: SupportTicket): Promise { + const detectedLanguage = await detectLanguage(ticket.content); + + if (detectedLanguage !== 'en') { + const translatedTicket = await translateTicket(ticket, detectedLanguage, 'en'); + const resolution = await processTicket(translatedTicket); + + if (resolution.response) { + resolution.response = await translateResponse(resolution.response, 'en', detectedLanguage); + } + + return resolution; + } + + return await processTicket(ticket); +} + +// Monitoring and Quality Assurance +export async function monitorSystemHealth(): Promise { + const metrics = await collectSystemMetrics(); + const alerts = []; + + if (metrics.automationAccuracy < 0.94) { + alerts.push({ type: 'accuracy_degradation', severity: 'high' }); + } + + if (metrics.responseTime > 30000) { // 30 seconds + alerts.push({ type: 'response_time_breach', severity: 'critical' }); + } + + if (metrics.safetyEscalationAccuracy < 0.999) { + alerts.push({ type: 'safety_accuracy_issue', severity: 'critical' }); + } + + return { + status: alerts.length === 0 ? 'healthy' : 'degraded', + metrics, + alerts, + timestamp: new Date() + }; +} + +// Constants +const AUTOMATABLE_INTENTS = [ + 'fare_adjustment', + 'receipt_request', + 'cancellation_dispute', + 'promo_issue', + 'eta_inquiry', + 'lost_item_report' +]; + +const SAFETY_KEYWORDS = [ + 'harassment', + 'assault', + 'accident', + 'emergency', + 'unsafe', + 'threatened', + 'injured' +]; +``` + +This TypeScript code represents RideResolve's core business processes as executable functions, covering customer acquisition, product development, revenue generation, operational procedures, and decision-making workflows. Each function includes proper error handling, async/await patterns, and represents specific business logic that could be implemented in a real system.