Testing & Optimization
Test your agents and optimize their performance using the playground and analytics
Agent Testing
The playground provides a safe environment to test your agents before deploying them to handle live customer conversations.
Testing Features
Conversation Simulation
Simulate real customer conversations to test agent responses. Try different scenarios, edge cases, and conversation flows.
Performance Metrics
Track response times, accuracy, and other key metrics during testing. Identify bottlenecks and optimization opportunities.
A/B Testing
Compare different agent configurations side by side. Test variations in personality, knowledge, or conversation flows.
Integration Testing
Test agent integrations with external systems. Verify data flow, authentication, and error handling.
Testing Process
- 1
Prepare Test Scenarios
Create realistic test scenarios based on common customer interactions
- 2
Run Tests
Execute test scenarios in the playground environment
- 3
Analyze Results
Review performance metrics and identify areas for improvement
- 4
Optimize Configuration
Adjust agent settings based on test results
Optimization Strategies
Response Quality
Improve the quality of agent responses:
- Knowledge Updates: Keep knowledge base current and relevant
- Training Data: Add more conversation examples for better learning
- Feedback Loops: Implement customer feedback mechanisms
- Regular Reviews: Periodically review and update agent configurations
Performance Tuning
Optimize agent performance:
- Response Speed: Minimize processing time for faster responses
- Resource Usage: Optimize memory and CPU usage for scalability
- Caching: Implement intelligent caching for frequently accessed data
- Load Balancing: Distribute conversations across multiple agent instances
Next Steps
Continue improving your agent: