Functional Requirements

This section outlines the critical functional requirements that drive the migration from legacy Enterprise Service Bus (ESB) architectures to the modern AI-enabled agentic commerce framework. These requirements address real-world challenges faced by enterprise organizations managing complex, multi-channel commerce ecosystems.

Core Problem Statement

Enterprise organizations currently face significant challenges with disconnected data stores and conflicting state management across their integrated systems. The legacy Websphere/Mulesoft architecture creates single-direction data overrides that result in out-of-sync data, exposing organizations to liability and operational inefficiencies.

The proposed architecture resolves these fundamental issues through unified data management, real-time consent services, and comprehensive idempotency controls.

Data Store Consolidation and State Management

Current State Challenges

Modern enterprise commerce operates across multiple disconnected systems:

Proposed Solution: Unified Data Layer

The new architecture implements Xano as the central data orchestration layer with Shopify as the AI-enabled Source of Truth for commerce data. This creates a unified, real-time view across all systems.

Key Features:

• Single Source of Truth: Shopify Global Catalog serves as the authoritative product database
• Real-Time Synchronization: Event-driven architecture ensures immediate data propagation
• Conflict Resolution: Idempotency management prevents data conflicts and duplicate processing
• State Consistency: JWE-secured session tokens maintain consistent state across all touchpoints

Real-Time Consent Services

Consent Management Architecture

User consent is managed as a first-class entity in the architecture, with real-time tracking and enforcement across all systems.

Consent Data Flow:

1. User provides or updates consent through any channel (Mobile, E-Com, POS, IoT)
2. Consent change triggers webhook to Xano consent service
3. Xano generates User Data Consent History JWE (cryptographically signed)
4. Consent state propagates to all connected systems via WebSocket
5. All systems enforce consent in real-time before data processing

Supported Consent Types:

• Marketing communications
• Data processing for personalization
• Third-party data sharing
• Cross-border data transfer
• AI/ML model training
• Analytics and tracking

Integration with UCP Session Management

Consent state is embedded in the UCP Session as part of the user's authenticated context. This ensures that every transaction, from product discovery to payment, respects the user's current consent preferences.

Webflow API Collections Integration:

• Webflow Collections connected to UCP Session and User History
• Consent updates flow through Xano/n8n hooks to Shopify/Google AI Data Stream
• Real-time consent state available to all AI agents

Secure Token Management

The architecture implements a two-tier token system to secure both sessions and transactions while maintaining comprehensive audit trails.

1. Session Tokens (JWE)

Purpose: Maintain stateful user sessions across distributed systems

Structure:

{
  "header": {
    "alg": "RSA-OAEP-256",
    "enc": "A256GCM"
  },
  "payload": {
    "user_id": "user_12345",
    "session_id": "sess_abc123xyz",
    "device_id": "device_789",
    "consent_version": "v3",
    "issued_at": 1705420800,
    "expires_at": 1705424400,
    "scope": ["commerce", "profile"]
  }
}

Security Features:

• Encrypted payload prevents tampering
• Short expiration (1 hour) limits exposure
• Device binding prevents token theft
• Consent version ensures compliance

2. Transaction Tokens (Linked to User ID with JWE History)

Purpose: Create immutable audit trail for all commerce transactions

Structure:

{
  "transaction_id": "txn_xyz789",
  "user_id": "user_12345",
  "session_id": "sess_abc123xyz",
  "mandate_chain": [
    {
      "type": "intent_mandate",
      "id": "intent_abc123",
      "timestamp": 1705420800,
      "signature": "..."
    },
    {
      "type": "cart_mandate",
      "id": "cart_xyz789",
      "timestamp": 1705420900,
      "signature": "..."
    }
  ],
  "payment_token": "tok_stripe_...",
  "consent_snapshot": {
    "version": "v3",
    "granted": ["data_processing", "payment"],
    "signature": "..."
  }
}

Audit Trail Benefits:

• Non-repudiable transaction history
• Consent state at time of transaction
• Complete mandate chain for accountability
• Regulatory compliance (PSD2, GDPR, CCPA)

Data Subject Rights (DSR) Reporting for Enterprise Organizations

DSR Compliance Framework

The architecture provides comprehensive support for Data Subject Rights under GDPR, CCPA, and similar regulations.

Supported DSR Operations:

Enterprise DSR Dashboard

Xano provides a centralized DSR Management Dashboard for enterprise organizations:

Features:

• Submit DSR requests on behalf of users
• Track request status across all systems
• Generate compliance reports
• Audit trail of all DSR operations
• Automated notifications to data processors

Multi-System Coordination:
When a DSR request is submitted, Xano orchestrates the request across all connected systems:

1. E-Commerce (Shopify): Order history, payment methods, addresses
2. CRM: Customer interactions, support tickets, preferences
3. WMS: Fulfillment history, returns, shipping data
4. POS: In-store purchase history
5. Mobile Apps: App usage data, push notification history
6. IoT Devices: Connected device data (if applicable)
7. ERP: Financial records (anonymized per retention policy)

Risk Mitigation: De-Risking Enterprise Liability

Problem: Out-of-Sync Data from Single-Direction Overrides

Legacy Architecture Risk:

Websphere and Mulesoft implement single-direction data flows where one system is the "master" and overrides all others. This creates several critical risks:

1. Data Loss: Updates in downstream systems are overwritten by scheduled batch jobs
2. Compliance Violations: Consent updates may not propagate before data processing occurs
3. Financial Liability: Incorrect pricing or tax calculations due to stale data
4. Customer Trust: Inconsistent experiences damage brand reputation
5. Audit Failures: No clear record of which system had correct data at any point in time

Real-World Scenario:

Customer updates email address in mobile app at 10:00 AM
→ Websphere batch job runs at 11:00 AM, overrides with old CRM data
→ Marketing email sent to old address at 11:30 AM
→ GDPR violation + customer complaint

Solution: Bidirectional Sync with Conflict Resolution

The new architecture implements bidirectional synchronization with intelligent conflict resolution:

Conflict Resolution Strategy:

Idempotency Management for Conflict Resolution:

Every data update includes an idempotency key that prevents duplicate processing and enables conflict detection:

Idempotency Key: sync:user_profile:user_12345:v7:1705420800

If two systems attempt to update the same data simultaneously:

1. First update succeeds, records idempotency key
2. Second update detects conflict via idempotency log
3. System compares timestamps and applies resolution strategy
4. Losing update is logged for audit purposes
5. All systems receive final reconciled state

Multi-Channel Data Resolution

Unified User Data Store

The architecture resolves user data across all enterprise touchpoints:

Channel Integration:

Google to Shopify E-Commerce Layer Management

The architecture positions Shopify as the E-Commerce Layer Management system for Google AI agents and other headless applications.

Integration Architecture:

Google AI Agent
    ↓ (A2A Protocol)
UCP Session Layer (Xano)
    ↓ (Catalog API)
Shopify Global Catalog
    ↓ (Checkout URL)
Merchant Shopify Store
    ↓ (Order Webhook)
Xano Order Management
    ↓ (Fulfillment API)
WMS/3PL Systems

Benefits:

• Google AI agents can discover and purchase products without custom integrations
• Shopify handles payment processing, fraud detection, and checkout optimization
• Xano orchestrates fulfillment across multiple warehouses
• Single integration point for all AI agents (Google, Amazon, custom)

Security Risk: Sequential Data vs. Socketed Encryption Service

The Risk of Sequential Data Processing

Legacy Approach (High Risk):

Traditional ESB architectures process data sequentially through multiple systems:

User submits payment → ESB receives → Writes to database → Reads from database 
→ Sends to payment gateway → Receives response → Writes to database 
→ Sends confirmation → Each step exposes unencrypted data

Security Vulnerabilities:

1. Data Exposure: Sensitive data (PII, payment info) exists in plaintext in multiple locations
2. Logging Risks: Sequential processing logs may contain unencrypted sensitive data
3. Memory Dumps: Data in transit through ESB can be captured in memory dumps
4. Audit Trail Gaps: Difficult to prove data was encrypted at every step
5. Compliance Failures: Does not meet PCI-DSS, HIPAA, or GDPR encryption requirements

Attack Vectors:

• Database compromise exposes all historical payment data
• ESB server compromise exposes data in transit
• Log file access reveals sensitive information
• Memory forensics can extract unencrypted data

Solution: Socketed Encryption Service Architecture

Modern Approach (Low Risk):

The new architecture implements end-to-end encryption with socketed services:

User submits payment (encrypted at client)
    ↓ (TLS 1.3 + JWE)
Xano Encryption Service (never decrypts)
    ↓ (Encrypted token)
Payment Gateway (decrypts in secure enclave)
    ↓ (Encrypted response)
Xano (stores encrypted token only)
    ↓ (Encrypted confirmation)
User receives confirmation

Security Advantages:

Socketed Encryption Implementation:

1. Client-Side Encryption: Payment data encrypted in browser/app using public key
2. Token Generation: Xano generates encrypted payment token without decrypting
3. Secure Transmission: Token sent to payment gateway via dedicated encrypted socket
4. Enclave Processing: Payment gateway decrypts in hardware security module (HSM)
5. Encrypted Storage: Only encrypted tokens stored in Xano database
6. Zero-Knowledge Architecture: Xano never has access to plaintext payment data

WebSocket Security for Real-Time Data:

For real-time consent and session management, the architecture uses authenticated WebSockets with per-message encryption:

// Establish secure WebSocket connection
const socket = new WebSocket('wss://xano.example.com/realtime');

// Authenticate with JWE token
socket.send(JSON.stringify({
  type: 'auth',
  token: userJweToken
}));

// All messages encrypted per-message
socket.send(encryptMessage({
  type: 'consent_update',
  consent: { marketing: false },
  signature: signConsent(...)
}));

Benefits:

• Real-time consent updates without data exposure
• Session state changes propagate instantly
• No plaintext data in transit logs
• Per-message authentication prevents replay attacks

Implementation Roadmap

Phase 1: Data Store Consolidation (Weeks 1-6)

• Implement Xano as central data orchestration layer
• Connect all existing data stores (CRM, E-Commerce, WMS, etc.)
• Establish idempotency management for conflict resolution
• Deploy real-time consent service

Phase 2: Token Security Implementation (Weeks 7-10)

• Deploy JWE session token system
• Implement transaction token with mandate chain
• Migrate to socketed encryption service
• Establish encrypted WebSocket connections

Phase 3: DSR Compliance (Weeks 11-14)

• Build DSR management dashboard
• Implement automated DSR request processing
• Create compliance reporting system
• Train enterprise teams on DSR workflows

Phase 4: Multi-Channel Integration (Weeks 15-20)

• Integrate all channels (Mobile, E-Com, POS, IoT, etc.)
• Deploy Google to Shopify AI agent integration
• Implement real-time data synchronization
• Decommission legacy Websphere/Mulesoft systems

Next: Detailed Architecture →