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·7 min read·Wisent Platform Team

Integrating AI Characters with Your Tech Stack

A practical guide to connecting AI characters with your existing enterprise systems including CRM, ticketing, communication platforms, and custom applications.

IntegrationTechnicalAPI

AI characters deliver the most value when they're deeply integrated with your existing technology ecosystem. A customer service character becomes exponentially more useful when it can access customer history from your CRM, create tickets in your support system, and communicate through your preferred channels. This guide covers integration strategies and best practices for enterprise environments.

Integration Architecture

The Integration Layer

We recommend building an integration layer that sits between your AI characters and backend systems. This layer:

  • Abstracts the complexity of individual integrations
  • Provides a unified interface for character access
  • Enables security controls and data transformation
  • Facilitates monitoring and debugging

    • Real-Time vs. Batch Integration

    Different use cases require different integration patterns:

    **Real-Time Integration** is essential when characters need immediate access to current data. A support character checking order status must query live data, not yesterday's export.

    **Batch Integration** works for less time-sensitive data like product catalogs or knowledge bases. Regular syncs keep AI knowledge current without the overhead of real-time queries.

    Most enterprise deployments use both patterns depending on data requirements.

    CRM Integration

    Salesforce

    Salesforce integration enables AI characters to:

  • Access customer profiles and interaction history
  • Create and update opportunities
  • Log conversation summaries as activities
  • Trigger automated workflows based on AI interactions

    • We provide a native Salesforce connector that handles authentication, rate limiting, and field mapping. For custom objects and complex workflows, our API enables programmatic integration.

    HubSpot

    HubSpot integration typically focuses on:

  • Contact enrichment from AI conversations
  • Lead qualification and scoring updates
  • Deal pipeline management
  • Marketing automation triggers

    • Microsoft Dynamics

    Dynamics 365 integration supports:

  • Customer service case management
  • Sales opportunity tracking
  • Customer insights enhancement
  • Field service scheduling

    • Ticketing and Support Platforms

    Zendesk

    Our Zendesk integration enables AI characters to:

  • Access ticket history and customer context
  • Create new tickets when escalation is needed
  • Update ticket fields and status
  • Add internal notes for human agents

    • The integration supports both real-time API calls and webhook-based updates.

    ServiceNow

    ServiceNow integration is particularly powerful for internal IT support:

  • Query knowledge base articles
  • Create and update incidents
  • Check asset information
  • Initiate automated workflows

    • Freshdesk

    Freshdesk integration supports:

  • Unified customer view across channels
  • Ticket creation and management
  • Canned response access
  • SLA tracking and alerts

    • Communication Platforms

    Slack

    Slack integration enables AI characters within your internal communication:

  • Respond to direct messages
  • Participate in channels (with appropriate permissions)
  • Access shared files and documents
  • Integrate with Slack workflows

    • Use cases include internal help desk, IT support, and employee onboarding assistance.

    Microsoft Teams

    Teams integration supports:

  • Personal chat with AI characters
  • Channel-based interactions
  • Integration with Teams apps and tabs
  • Meeting assistance and follow-up

    • Custom Chat Widgets

    For customer-facing applications, embed AI characters through:

  • JavaScript widget for web applications
  • React and Vue components for modern frontends
  • Native SDKs for mobile applications
  • API-first approach for complete customization

    • Knowledge Base Integration

    Document Sources

    AI characters often need access to organizational knowledge:

  • Confluence and SharePoint wikis
  • Google Drive and Dropbox documents
  • Internal documentation repositories
  • Structured databases

    • Our platform supports intelligent document processing that:

  • Extracts and indexes content
  • Maintains source attribution
  • Updates automatically when documents change
  • Respects access permissions

    • Vector Databases

    For semantic search capabilities, we integrate with:

  • Pinecone for managed vector storage
  • Weaviate for self-hosted deployments
  • Elasticsearch with vector capabilities
  • Custom vector store implementations

    • API Integration

    RESTful APIs

    Our primary API is RESTful, enabling straightforward integration:

  • Standard HTTP methods (GET, POST, PUT, DELETE)
  • JSON request and response bodies
  • OAuth 2.0 authentication
  • Comprehensive endpoint documentation

    • Webhooks

    For event-driven architecture, configure webhooks for:

  • Conversation events (started, ended, escalated)
  • Character events (updated, published)
  • System events (errors, threshold alerts)

    • Webhooks include signature verification for security.

    GraphQL

    For complex data requirements, our GraphQL API enables:

  • Efficient data fetching in a single request
  • Strong typing for reliable integration
  • Subscriptions for real-time updates
  • Introspection for API discovery

    • Integration Best Practices

    Error Handling

    Build robust error handling:

  • Implement retry logic with exponential backoff
  • Handle timeout scenarios gracefully
  • Log failures for debugging
  • Provide fallback responses when integrations fail

    • Rate Limiting

    Respect and implement rate limits:

  • Understand limits of integrated systems
  • Implement client-side rate limiting
  • Queue non-urgent requests
  • Cache frequently accessed data

    • Data Transformation

    Often, data needs transformation between systems:

  • Map fields between different schemas
  • Handle data type conversions
  • Sanitize sensitive information
  • Validate data before sending

    • Testing Integration

    Thorough testing is essential:

  • Unit tests for transformation logic
  • Integration tests with sandbox environments
  • Load tests for high-volume scenarios
  • Chaos engineering for failure scenarios

    • Security Considerations

    Credential Management

    Secure all integration credentials:

  • Use vault solutions (HashiCorp Vault, AWS Secrets Manager)
  • Rotate credentials regularly
  • Implement least-privilege access
  • Audit credential usage

    • Data Minimization

    Only sync necessary data:

  • Map specific fields, not entire records
  • Filter sensitive information
  • Implement data retention policies
  • Honor privacy preferences

    • Audit Trail

    Maintain integration audit logs:

  • Log all data access
  • Track data transformations
  • Record integration errors
  • Enable compliance reporting

    • Getting Started

    Integration Planning

    Before building integrations:

  • Map your current technology landscape
  • Identify high-value integration targets
  • Assess security and compliance requirements
  • Plan phased implementation

    • Implementation Support

    Wisent Platform provides:

  • Pre-built connectors for popular platforms
  • API documentation and SDKs
  • Integration templates and examples
  • Professional services for custom needs

    • Start with a single integration, prove value, then expand systematically. Our team can help you build an integration roadmap aligned with your business priorities.

    Ready to Transform Your Enterprise?

    See how Wisent Platform can help your organization deploy AI characters at scale.

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