Worker Agent Realtime

Realtime worker agent guide

Real-Time API Configuration

Real-Time Worker Agent enables live, conversational interactions with your Worker Agent, providing instant responses and seamless user experiences. This guide covers configuring and optimizing real-time features for your agents.

Understanding Real-Time API

Real-Time API transforms your Knowledge Agent into a dynamic, conversational interface that:

• Provides instant responses - No waiting for batch processing or delayed replies
• Enables live conversations - Natural back-and-forth interactions
• Supports voice integration - Compatible with voice-based interactions
• Maintains conversation context - Remembers previous exchanges within sessions

Live Interactions

Instant responses for real-time user engagement

Voice Compatible

Works seamlessly with Aivah’s voice interaction features

Context Retention

Maintains conversation flow and remembers previous questions

Scalable Performance

Handles multiple simultaneous conversations efficiently

When to Enable Real-Time API

Ideal Use Cases

Customer Support

• Live chat support on websites
• Instant FAQ responses
• Real-time troubleshooting assistance
• Immediate customer service interactions

Interactive Learning

• Educational Q&A sessions
• Training modules with instant feedback
• Interactive presentations
• Real-time tutoring assistance

Sales and Marketing

• Live product demonstrations
• Instant pricing and feature queries
• Real-time lead qualification
• Interactive sales presentations

Internal Tools

• Employee self-service portals
• IT help desk automation
• Policy and procedure assistance
• Real-time information access

When NOT to Use Real-Time API

• Batch processing scenarios - When responses can be processed in groups
• Static information delivery - Simple, one-way information sharing
• Limited interaction needs - Minimal user engagement expected
• Cost-sensitive applications - When response speed isn’t critical

Enabling Real-Time API

During Agent Creation

1. Access Agent Creation

   Navigate to Knowledge → Create New Agent in your Aivah dashboard.

2. Configure Basic Settings

   Enter your agent name and configure the presentation mode as needed.

3. Enable Real-Time API

   Toggle the Real-Time API switch to ON during the creation process.

4. Complete Agent Setup

   Add your knowledge content and click + Create to finalize the agent.

For Existing Agents

1. Access Agent Settings

   Select your existing agent from the Knowledge workspace sidebar.

2. Edit Configuration

   Look for the Real-Time API toggle in your agent settings.

3. Enable Feature

   Switch the Real-Time API toggle to ON.

4. Save Changes

   Confirm the changes and allow the system to update your agent configuration.

Enabling Real-Time API may affect your usage costs based on your Aivah plan. Check your plan details for real-time interaction pricing.

Real-Time Configuration Options

Response Optimization

Speed Settings

Optimize for Response Time

• Prioritize quick responses over comprehensive answers
• Ideal for simple Q&A and quick information retrieval
• Best for high-volume, brief interactions
• Reduces processing time for faster user experience

Quality Settings

Optimize for Response Quality

• Prioritize comprehensive, detailed responses
• Better for complex questions requiring thorough explanations
• Ideal for educational or consultative interactions
• May have slightly longer response times

Balanced Settings

Optimize for Both

• Balance speed and quality based on query complexity
• Adapts response style to question type
• Good default setting for most use cases
• Automatically adjusts based on interaction context

Context Management

1. Session Duration

   Configure how long conversation context is maintained:

   • Short sessions (5-10 minutes): Quick interactions
   • Medium sessions (30-60 minutes): Extended conversations
   • Long sessions (2+ hours): Deep consultative interactions
2. Context Depth

   Set how many previous interactions to remember:

   • Shallow context (2-3 exchanges): Simple Q&A
   • Medium context (5-10 exchanges): Standard conversations
   • Deep context (10+ exchanges): Complex, multi-topic discussions
3. Context Reset

   Define when context should reset:

   • Auto-reset after periods of inactivity
   • Manual reset when users start new topics
   • Never reset for continuous long-form interactions

Integration and Implementation

Web Integration

1. Generate API Credentials

   Access your agent’s Share settings to generate API keys and endpoints.

2. Implement Chat Interface

   Use Aivah’s JavaScript SDK or REST API to integrate real-time chat:

   // Example integration code
   const aivahChat = new AivahRealTimeAPI({
     agentId: 'your-agent-id',
     apiKey: 'your-api-key'
   });
   
   aivahChat.sendMessage('Hello, I need help with...')
     .then(response => {
       displayResponse(response.message);
     });
   
3. Handle Real-Time Events

   Set up event listeners for:

   • Message sending and receiving
   • Typing indicators
   • Connection status
   • Error handling

Voice Integration

Voice Input Setup

Configure your agent to accept voice input:

• Enable microphone access in your application
• Use speech-to-text conversion
• Pass converted text to Real-Time API
• Handle audio input processing

Voice Output Configuration

Set up text-to-speech for responses:

• Choose appropriate voice models
• Configure speech rate and tone
• Handle audio output to users
• Manage voice playback controls

Voice Experience Optimization

Optimize for voice interactions:

• Adjust response length for audio
• Use conversational language patterns
• Include audio-friendly formatting
• Handle voice-specific user intents

Performance Optimization

Response Time Optimization

1. Knowledge Base Optimization

   Optimize your content for faster retrieval:

   • Remove redundant or outdated information
   • Structure content with clear headings
   • Use concise, well-organized documents
   • Regularly clean up knowledge base
2. Query Optimization

   Help users ask better questions:

   • Provide suggested questions or prompts
   • Guide users toward specific information
   • Use autocomplete or query suggestions
   • Implement query refinement features
3. Caching Strategy

   Implement intelligent caching:

   • Cache frequently asked questions
   • Pre-load common response patterns
   • Use session-based caching for repeated queries
   • Implement smart cache invalidation

Scalability Considerations

Concurrent Users

Monitor and plan for peak usage times with multiple simultaneous conversations

Resource Management

Optimize resource allocation for consistent performance under load

Response Queuing

Implement proper queuing for high-volume periods

Load Balancing

Distribute traffic effectively across available resources

Monitoring and Analytics

Real-Time Metrics

Track key performance indicators:

• Response time - Average time from query to response
• Conversation length - Number of exchanges per session
• User satisfaction - Ratings and feedback scores
• Completion rate - Percentage of successfully resolved interactions
• Error rates - Failed or incomplete responses

Usage Analytics

Peak Usage Patterns

Identify when your agent is most active:

• Daily usage peaks and valleys
• Weekly patterns and trends
• Seasonal usage variations
• Geographic usage distribution

Common Interaction Patterns

Understand how users interact:

• Most frequent question types
• Common conversation flows
• Average session duration
• Popular knowledge areas

Performance Trends

Track improvement over time:

• Response quality improvements
• Speed optimization results
• User satisfaction trends
• Knowledge base effectiveness

Troubleshooting Real-Time Issues

Slow Response Times

Common Causes:

• Overloaded knowledge base
• Complex queries requiring extensive processing
• Network connectivity issues
• High concurrent user load

Solutions:

• Optimize and streamline knowledge content
• Implement query complexity handling
• Check network infrastructure
• Scale resources during peak times

Connection Issues

Possible Problems:

• API endpoint connectivity
• Authentication failures
• Network timeouts
• Service interruptions

Troubleshooting Steps:

• Verify API credentials and endpoints
• Check network connectivity
• Implement retry logic with backoff
• Monitor service status

Context Loss

Symptoms:

• Agent forgets previous conversation
• Inconsistent responses
• Loss of session continuity

Fixes:

• Check session timeout settings
• Verify context retention configuration
• Implement proper session management
• Review conversation flow logic

Best Practices for Real-Time Agents

User Experience

• Provide clear feedback during processing
• Implement typing indicators for better UX
• Handle errors gracefully with helpful messages
• Offer alternative suggestions when agent can’t help

Performance

• Regular performance monitoring and optimization
• Implement proper error handling and recovery
• Use efficient data structures and algorithms
• Plan for scalability from the beginning

Content Strategy

• Keep knowledge base focused and current
• Regular content audits and updates
• Test agent responses with real user scenarios
• Continuously improve based on usage patterns

Advanced Real-Time Features

Multi-Modal Integration

Combine real-time text with other media:

• Image processing - Analyze and respond to uploaded images
• Document upload - Process documents during conversations
• Screen sharing - Integrate with visual assistance tools
• Video integration - Handle video content in real-time interactions

Workflow Integration

1. Connect External Systems

   Integrate with CRM, ticketing, or other business systems for seamless workflows.

2. Implement Handoff Procedures

   Set up smooth transitions to human agents when needed.

3. Automate Follow-Up

   Configure automated follow-up messages and actions based on conversation outcomes.

Ready to explore different agent configurations? Learn about the various Types of Agents or return to the main Knowledge Agent Overview.