---

title: "ServiceAI Platform Technical Specification" project: "ServiceAI Platform" version: "2.0.0" status: "Draft" author: "Engineering Team" reviewers:

• "Sarah Chen, Architecture"
• "Mike Johnson, Security"
• "Lisa Park, Infrastructure" last_updated: "2024-03-15"

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ServiceAI Platform Technical Specification

Overview

This technical specification outlines the architecture, components, and implementation details for version 2.0 of the ServiceAI Platform. The platform provides AI-powered customer service automation with enhanced security, scalability, and integration capabilities.

Table of Contents

1. System Architecture
2. Components
3. Data Flow
4. APIs
5. Security
6. Performance
7. Deployment
8. Testing

1. System Architecture

1.1 High-Level Architecture

graph TD
    A[Client Applications] --> B[API Gateway]
    B --> C[Load Balancer]
    C --> D[Application Servers]
    D --> E[AI Engine]
    D --> F[Database Cluster]
    E --> G[Model Registry]
    E --> H[Training Pipeline]

1.2 Key Components

1. API Gateway

   • Rate limiting
   • Authentication
   • Request routing

2. Application Servers

   • Stateless design
   • Horizontal scaling
   • Request handling

3. AI Engine

   • Model serving
   • Real-time inference
   • Training coordination

2. Components

2.1 API Gateway

component:
  name: API Gateway
  technology: AWS API Gateway
  configuration:
    rate_limit: 1000 req/min
    timeout: 30s
    cors: enabled
    auth:
      - JWT
      - API Keys

2.2 Application Servers

class ApplicationServer:
    def __init__(self):
        self.config = self.load_config()
        self.ai_engine = AIEngine()
        self.db = DatabaseConnection()
        
    async def handle_request(self, request):
        """
        Process incoming API requests
        """
        try:
            validated_data = self.validate(request)
            response = await self.process(validated_data)
            return self.format_response(response)
        except Exception as e:
            return self.handle_error(e)

3. Data Flow

3.1 Request Processing

1. Client Request

POST /api/v2/analyze
Content-Type: application/json
Authorization: Bearer <token>

{
  "text": "How do I reset my password?",
  "context": {
    "user_id": "12345",
    "language": "en"
  }
}

1. Response

{
  "intent": "password_reset",
  "confidence": 0.95,
  "suggested_action": {
    "type": "workflow",
    "id": "pw_reset_001"
  },
  "response": {
    "text": "I can help you reset your password...",
    "links": [
      {
        "text": "Reset Password",
        "url": "/password-reset"
      }
    ]
  }
}

4. APIs

4.1 REST Endpoints

4.2 WebSocket API

interface WSMessage {
  type: 'message' | 'status' | 'error';
  payload: {
    text?: string;
    status?: string;
    code?: number;
  };
  timestamp: number;
}

5. Security

5.1 Authentication

• JWT-based authentication
• API key management
• Role-based access control

5.2 Data Protection

• End-to-end encryption
• Data masking
• Audit logging

6. Performance

6.1 Requirements

6.2 Scaling Strategy

• Horizontal scaling
• Auto-scaling policies
• Load balancing

7. Deployment

7.1 Infrastructure

infrastructure:
  provider: AWS
  regions:
    - us-east-1
    - eu-west-1
    - ap-southeast-1
  services:
    - EKS
    - RDS
    - ElastiCache
    - S3

7.2 CI/CD Pipeline

1. Build Stage

   • Code compilation
   • Unit tests
   • Security scans

2. Test Stage

   • Integration tests
   • Performance tests
   • Security tests

3. Deploy Stage

   • Blue-green deployment
   • Canary releases
   • Rollback procedures

8. Testing

8.1 Test Strategy

def test_analyze_endpoint():
    """
    Test the analyze endpoint with various inputs
    """
    test_cases = [
        {
            "input": "password reset request",
            "expected": {
                "intent": "password_reset",
                "confidence": 0.9
            }
        },
        # More test cases...
    ]
    
    for case in test_cases:
        response = client.post("/analyze", json=case["input"])
        assert response.status_code == 200
        assert response.json()["intent"] == case["expected"]["intent"]

8.2 Performance Testing

• Load testing scenarios
• Stress testing parameters
• Endurance testing duration

Appendix

A. Dependencies

B. Monitoring

• Metrics collection
• Alert thresholds
• Dashboard configuration

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Last Updated: March 15, 2024 Version: 2.0