Examples & Use Cases

Reactive Agents provides comprehensive AI agent optimization across various industries and use cases. Here are real-world examples of how organizations use Reactive Agents to improve their AI systems.

AI Agent Optimization

Automatic Performance Improvement

• Intelligent Clustering: Automatically group similar conversations for targeted optimization
• Thompson Sampling: Continuously learn and select optimal AI configurations
• Real-time Evaluation: Monitor performance with 7 built-in evaluation methods
• Multi-Provider Support: Compare and optimize across 35+ AI providers
• Continuous Learning: System automatically improves over time without manual intervention

Production Monitoring & Analytics

• Performance Tracking: Monitor response times, success rates, and quality metrics
• Usage Analytics: Understand AI system usage patterns and optimization opportunities
• Request Tracing: Track requests across services with distributed tracing
• Cache Optimization: Monitor cache hit rates and performance improvements

Integration Examples

const response = await fetch('http://localhost:3000/v1/chat/completions', {
  method: 'POST',
  headers: {
    'Authorization': `Bearer ${process.env.BEARER_TOKEN ?? 'reactive-agents'}`,
    'Content-Type': 'application/json',
    'ra-config': JSON.stringify({
      agent_name: 'customer-support',
      skill_name: 'email-processing',
      strategy: { mode: 'single' },
      targets: [{
        optimization: 'auto'
      }]
    }),
  },
  body: JSON.stringify({
    model: 'gpt-5',
    messages: [
      { role: 'user', content: 'Help me respond to this customer email' }
    ],
  }),
});

const data = await response.json();

import requests
import json
import os

response = requests.post(
    'http://localhost:3000/v1/chat/completions',
    headers={
        'Authorization': `Bearer ${process.env.BEARER_TOKEN ?? 'reactive-agents'}`,
        'Content-Type': 'application/json',
        'ra-config': json.dumps({
            'agent_name': 'data-analyst',
            'skill_name': 'data-analysis',
            'strategy': {'mode': 'single'},
            'targets': [{
                'optimization': 'auto'
            }]
        })
    },
    json={
        'model': 'gpt-5',
        'messages': [
            {'role': 'user', 'content': 'Analyze this data and provide insights'}
        ]
    }
)

data = response.json()

curl -X POST http://localhost:3000/v1/chat/completions \
  -H "Authorization: Bearer ${process.env.BEARER_TOKEN:-reactive-agents}" \
  -H "Content-Type: application/json" \
  -H "ra-config: {\"agent_name\":\"content-creator\",\"skill_name\":\"blog-writing\",\"strategy\":{\"mode\":\"single\"},\"targets\":[{\"optimization\":\"auto\"}]}" \
  -d '{
    "model": "gpt-5",
    "messages": [
      {"role": "user", "content": "Write a blog post about AI trends"}
    ]
  }'

Use Case Studies

Customer Support Automation

• Agent: customer-support
• Skill: email-processing
• Evaluation Methods: Task Completion, Turn Relevancy, Role Adherence
• Optimization: Automatic clustering groups similar customer issues, Thompson Sampling selects optimal response strategies
• Improvement: System learns from evaluation feedback to improve response quality and reduce resolution time

Content Generation

• Agent: content-creator
• Skill: blog-writing
• Evaluation Methods: Argument Correctness, Knowledge Retention, Conversation Completeness
• Optimization: Clustering identifies content patterns, automatic optimization improves writing quality
• Improvement: Continuous learning from evaluation scores optimizes content structure and accuracy

Data Analysis

• Agent: data-analyst
• Skill: data-analysis
• Evaluation Methods: Task Completion, Argument Correctness, Knowledge Retention
• Optimization: Intelligent routing selects best AI models for different analysis types
• Improvement: Performance tracking identifies optimal analysis approaches and model configurations

E-commerce Chatbot

• Agent: ecommerce-bot
• Skill: product-recommendations
• Evaluation Methods: Tool Correctness, Turn Relevancy, Role Adherence
• Optimization: Clustering groups customer preferences, automatic optimization improves recommendation accuracy
• Improvement: Real-time evaluation feedback enhances product matching and customer satisfaction

Healthcare Assistant

• Agent: healthcare-assistant
• Skill: symptom-analysis
• Evaluation Methods: Task Completion, Argument Correctness, Role Adherence
• Optimization: Multi-provider support ensures reliable responses, clustering improves diagnostic accuracy
• Improvement: Continuous evaluation ensures medical information accuracy and appropriate responses