Technical Architecture
This document describes the AI Wallet system architecture with detailed GTM technical strategy, covering gateway integration, policy edge design, and router-agnostic implementation. Objective: Define scalable architecture that supports rapid market entry while maintaining flexibility to integrate with multiple AI providers and gateways.
Executive Summary
Based on GTM analysis, AI Wallet's technical strategy focuses on: - Router-Agnostic Design: Integration with existing gateways (OpenRouter, Vercel AI Gateway) rather than building own router - Policy Edge Architecture: Lightweight middleware for budget enforcement and consent management - Identity-First Approach: Cross-app user identity and consent receipts as core differentiator - Ephemeral Key Management: Secure, short-lived credentials for API access - Modular Integration: Plug-and-play compatibility with developer workflows
Core Architecture Principles
GTM-Derived Design Decisions
1. Gateway Integration Over Building - Strategy: Integrate with existing gateways rather than compete as another router - Rationale: Leverages proven infrastructure while focusing differentiation on identity layer - Providers: OpenRouter (PKCE + credits), Vercel AI Gateway (team billing), Cloudflare AI Gateway - Benefits: Faster time-to-market, reduced infrastructure complexity, partner-friendly positioning
2. Policy Edge Proxy Pattern - Design: Thin server middleware that enforces policies before reaching backend providers - Functions: Budget validation, consent checking, usage metering, rate limiting - Security: Short-lived session tokens, no provider keys exposed to clients - Performance: Minimal latency overhead, optimized for high-throughput API calls
3. Identity-Native Architecture - Core Value: Cross-app user identity that travels with users across different applications - Implementation: OAuth-based authentication with portable consent receipts - Data Model: User-centric usage analytics and spending governance - Compliance: Built-in audit trails and regulatory reporting
System Architecture
High-Level Architecture
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ Client App │ │ Client App │ │ Client App │
│ (Next.js/React)│ │ (Mobile) │ │ (CLI) │
└─────────┬───────┘ └─────────┬───────┘ └─────────┬───────┘
│ │ │
└──────────────────────┼──────────────────────┘
│
┌────────────▼────────────┐
│ AI Wallet SDK │
│ - Authentication │
│ - Budget Management │
│ - Consent Receipts │
└────────────┬────────────┘
│
┌────────────▼────────────┐
│ Policy Edge Proxy │
│ - Session Validation │
│ - Budget Enforcement │
│ - Usage Metering │
│ - Consent Verification │
└────────────┬────────────┘
│
┌──────────────────────┼──────────────────────┐
│ │ │
┌─────▼─────┐ ┌─────▼─────┐ ┌─────▼─────┐
│ OpenRouter│ │ Vercel AI │ │ Cloudflare│
│ PKCE │ │ Gateway │ │ AI Gateway│
└───────────┘ └───────────┘ └───────────┘
Component Architecture
1. AI Wallet SDK Layer
Purpose: Developer-friendly client library for easy integration Key Components: - WalletProvider: React context for wallet state management - useWallet(): Hook for accessing wallet functionality - Auth Components: Login, consent, and billing UI components - API Client: Encrypted communication with policy edge
GTM Integration Features: - Drop-in React components for quick implementation - Framework-agnostic API for non-React applications - Automatic consent receipt generation - Built-in budget visualization and controls
2. Policy Edge Proxy
Purpose: Centralized policy enforcement and usage metering Architecture: - API Gateway: Handles incoming requests with authentication - Session Manager: Validates short-lived session tokens - Policy Engine: Enforces budget, rate, and consent policies - Usage Tracker: Real-time metering and analytics - Consent Manager: Validates and updates consent receipts
Security Model: - Ephemeral Tokens: 5-15 minute session tokens, no long-lived credentials - Key Isolation: Provider API keys never exposed to client applications - Audit Logging: Immutable record of all policy decisions and API calls - Encryption: End-to-end encryption for sensitive data
3. Gateway Adapters
Purpose: Abstract integration with different AI providers Adapter Pattern Implementation:
interface GatewayAdapter {
// Unified interface for all gateways
authenticate(user: User, scopes: string[]): Promise<AuthResult>;
call(request: AIRequest): Promise<AIResponse>;
getUsage(userId: string): Promise<UsageData>;
validateBudget(userId: string, amount: number): Promise<boolean>;
}
// Specific implementations
class OpenRouterAdapter implements GatewayAdapter { ... }
class VercelGatewayAdapter implements GatewayAdapter { ... }
class CloudflareAdapter implements GatewayAdapter { ... }
Router Selection Strategy: - Default: Vercel AI Gateway (best developer experience) - User Choice: OpenRouter (if user has account and wants it) - Enterprise: Direct provider connections (for compliance) - Fallback: Load balancing across available providers
4. Identity and Consent Management
Purpose: Cross-app identity with portable consent Components: - User Identity Service: OAuth-based authentication with cross-app identity - Consent Receipt System: Cryptographically signed consent records - Policy Engine: Centralized policy management and enforcement - Audit Trail: Immutable consent and usage history
Data Architecture
Core Data Models
User Model:
interface User {
id: string;
email: string;
walletId: string;
consentReceipts: ConsentReceipt[];
budgets: Budget[];
usage: UsageRecord[];
preferences: UserPreferences;
}
Consent Receipt Model:
interface ConsentReceipt {
id: string;
userId: string;
appId: string;
scopes: string[];
issuedAt: Date;
expiresAt: Date;
signature: string; // Cryptographic signature
revocationToken: string;
}
Budget Model:
interface Budget {
id: string;
userId: string;
appId?: string; // Optional per-app budget
amount: number;
period: 'daily' | 'weekly' | 'monthly';
resetDate: Date;
spent: number;
currency: 'credits' | 'usd';
}
Data Flow Architecture
Authentication Flow: 1. User authenticates with AI Wallet 2. AI Wallet validates user and checks budgets 3. Policy Edge issues short-lived session token 4. Client uses token to make API calls 5. Gateway adapters handle provider-specific authentication
API Call Flow: 1. Client sends request with session token 2. Policy Edge validates token and policies 3. Usage tracked and budget checked 4. Request forwarded to appropriate gateway adapter 5. Response returned with usage metadata 6. Audit trail updated
Consent Management Flow: 1. App requests specific scopes 2. User presented with clear consent interface 3. Consent receipt generated and signed 4. Receipt stored with cryptographic integrity 5. Policy Edge validates consent on each API call
Security Architecture
Key Management Strategy
GTM-Derived Security Requirements: - No Client-Side Provider Keys: All provider API keys stay on server - Ephemeral Credentials: Short-lived tokens minimize exposure risk - Zero-Knowledge: Client never sees provider-specific implementation - Audit-Ready: All actions logged for compliance
Implementation: - Key Vault: Encrypted storage of all provider API keys - Rotation: Automatic key rotation every 30 days - Monitoring: Real-time detection of key usage anomalies - Revocation: Immediate key invalidation capability
Privacy by Design
Data Minimization: - Collect only necessary data for billing and compliance - Anonymize usage data where possible - Implement data retention policies - Support data deletion requests
Cross-Border Compliance: - Regional data residency options - GDPR-compliant data processing - Audit trail for data access - Consent-based data sharing
Scalability and Performance
Horizontal Scaling Strategy
Stateless Design: - Policy Edge proxy designed for horizontal scaling - Session state stored in Redis cluster - Gateway adapters can scale independently - Database read replicas for global performance
Performance Targets: - API Latency: < 50ms added latency for policy enforcement - Throughput: 10,000+ requests per second per instance - Availability: 99.9% uptime SLA - Data Consistency: Eventual consistency acceptable for usage tracking
Load Balancing and Failover
Multi-Region Deployment: - Primary: US East (Virginia) - Secondary: EU West (Ireland) - Tertiary: Asia Pacific (Singapore) - Automatic failover between regions
Provider Redundancy: - Primary: Vercel AI Gateway - Fallback: OpenRouter - Emergency: Direct provider APIs - Circuit breaker pattern for provider failures
GTM-Specific Technical Features
Developer Experience Focus
Quick Integration:
- One-line SDK integration: <AIWalletProvider>
- Automatic consent UI generation
- Built-in budget visualization
- TypeScript definitions for all APIs
Documentation and Examples: - Interactive API documentation - Code examples in multiple languages - Video tutorials for common use cases - Integration testing sandbox
Partnership-Friendly Architecture
White-Label Options: - Customizable branding for partners - API access for custom integrations - Revenue sharing through usage tracking - Partner-specific features and controls
Open Standards Support: - OpenID Connect for authentication - OAuth 2.0 for authorization - JSON Web Tokens for sessions - RESTful APIs for integrations
Monitoring and Observability
Technical Metrics
- Performance: API latency, throughput, error rates
- Usage: Requests per second, data transfer, cache hit rates
- Business: Revenue, user adoption, partner usage
- Security: Authentication failures, policy violations, key usage
Compliance Monitoring
- Audit Logs: All policy decisions and API calls
- Consent Tracking: Consent changes and revocations
- Data Access: Who accessed what data when
- Regulatory Reports: Automated compliance reporting
Deployment and DevOps
Infrastructure as Code
- Terraform: Multi-cloud infrastructure provisioning
- Kubernetes: Container orchestration
- Helm: Application deployment and scaling
- ArgoCD: GitOps continuous deployment
CI/CD Pipeline
- GitHub Actions: Automated testing and deployment
- Security Scanning: SAST/DAST in pipeline
- Performance Testing: Automated load testing
- Blue-Green Deployment: Zero-downtime deployments
Migration and Integration Strategy
Provider Migration
- Gradual Migration: Move users to new providers gradually
- A/B Testing: Test different provider configurations
- Fallback Mechanisms: Automatic provider switching
- User Notification: Transparent communication about changes
Data Migration
- Backward Compatibility: Support legacy API versions
- Data Import: Tools for importing existing user data
- Progressive Enhancement: New features without breaking changes
- Rollback Capability: Quick rollback for problematic changes
Future Architecture Considerations
AI-Specific Features
- Model Preference Learning: User-specific model recommendations
- Cost Optimization: Automatic routing to most cost-effective models
- Performance Monitoring: Model-specific performance tracking
- A/B Testing: Built-in experimentation framework
Enterprise Features
- Multi-Tenancy: Support for enterprise customer hierarchies
- Advanced Analytics: Usage patterns and cost optimization insights
- Custom Policies: Enterprise-specific budget and access policies
- Integration APIs: Enterprise system integration capabilities
Core Architecture Components (Whitepaper View)
Based on the AI Wallet whitepaper, the system consists of six foundational layers:
1. Gateway/API Layer
- Function: Single REST/gRPC endpoint routes requests to configured AI backends
- Features: Fault-tolerant routing, retries, and regional load balancing
- Implementation: Unified API surface that abstracts provider differences
2. Provider Adapters
- Function: Pluggable modules translating standard calls into provider-specific formats
- Support: Custom or self-hosted models alongside major provider integrations
- Benefits: Extensibility for new providers without core system changes
3. Billing & Usage Engine
- Function: Real-time metering (tokens, compute seconds, calls)
- Features: Tiered subscription and pay-as-you-go billing
- Capabilities: Automated invoicing and payment reconciliation
4. Identity & Entitlements
- Function: OAuth/OIDC integration for developer and end-user auth
- Features: Role-based access controls and fine-grained usage policies
- Security: Token vaulting and secure key management
5. Dashboard & Analytics
- Function: Unified usage dashboards, cost breakdowns, latency and error metrics
- Features: Alerts, quotas, and predictive cost modeling
- Value: Visibility and control for all stakeholders
6. Partner & Marketplace Layer
- Function: Onboarding flows for third-party model and data vendors
- Features: Revenue-share management and contract enforcement
- Strategy: Ecosystem growth and network effects
Source: AI Wallet_ A Next-Generation Infrastructure for AI.md lines 19-41
Source Attribution
Primary source for technical strategy: GTM-01Nov25-ChatGPTPlus.pdf Architecture components: AI Wallet_ A Next-Generation Infrastructure for AI.md