Claude Agents for Business Process Automation: Enterprise Guide

# Claude Enterprise Integration Configuration
integration:
  authentication:
    type: "oauth2"
    provider: "azure_ad"
    gateway: "api_management"
  
  connectors:
    - name: "salesforce"
      type: "mcp_server"
      auth: "oauth2"
      endpoints:
        - accounts
        - opportunities
        - cases
    
    - name: "sap"
      type: "direct_api"
      protocol: "odata_v4"
      security: "certificate"
    
    - name: "microsoft_365"
      type: "graph_api"
      scopes:
        - mail.read
        - files.readwrite
        - teams.read
  
  orchestration:
    pattern: "hub_and_spoke"
    workers: 10
    max_parallel: 25
    timeout: 300
  
  monitoring:
    metrics: "prometheus"
    logging: "elasticsearch"
    tracing: "jaeger"

# Enterprise Agent Orchestrator Pattern
from anthropic import AsyncAnthropic
import asyncio
from typing import List, Dict

class EnterpriseOrchestrator:
    def __init__(self, api_key: str):
        self.client = AsyncAnthropic(api_key=api_key)
        self.workers = {}
        self.metrics = MetricsCollector()
    
    async def process_workflow(self, 
                              workflow: Dict,
                              context: Dict) -> Dict:
        """Orchestrate complex business process"""
        # Decompose into parallel tasks
        tasks = self.decompose_workflow(workflow)
        
        # Execute in parallel with rate limiting
        results = await asyncio.gather(*[
            self.execute_task(task, context)
            for task in tasks
        ])
        
        # Aggregate and validate results
        return self.aggregate_results(results)
    
    async def execute_task(self, 
                          task: Dict,
                          context: Dict) -> Dict:
        """Execute individual task with retry logic"""
        retry_count = 0
        max_retries = 3
        
        while retry_count < max_retries:
            try:
                response = await self.client.messages.create(
                    model="claude-3-5-sonnet-20241022",
                    max_tokens=4000,
                    system=task['agent_prompt'],
                    messages=[{
                        "role": "user",
                        "content": task['instruction']
                    }]
                )
                
                # Track metrics
                self.metrics.record(task, response)
                return response
                
            except Exception as e:
                retry_count += 1
                await asyncio.sleep(2 ** retry_count)
        
        raise ProcessingError(f"Task failed: {task['id']}")