Integration Methods

The CRM offers multiple integration methods to seamlessly connect with various data sources, ensuring that businesses can efficiently leverage their data within the CRM. These integration methods cater to diverse technical environments and operational needs, providing flexibility for different types of users.

API-Based Integration (push)

API-based integration that enables the customer to push data via REST APIs to the CRM. This method of integration is recommended for small to medium sized organisations and supports real-time data.

Supported API Types

• REST APIs (JSON)

Key Benefits

• Real-time data (if events are pushed in real-time)
• Predefined data structures

Integration Process

1. Access – API keys, documentation and credentials are supplied to the customer.
2. Integration – All APIs are integrated and  historical data (up to 6 months data) is pushed to the CRM.
3. Scheduling & Automation – Data can be pushed to the API in real-time as events occur, or scheduled in a batch format.

Security Considerations

• API key
• IP whitelisting
• Data encryption during transmission
• Rate limiter and API monitoring

⚠️ Technical information about API push integration is available in the Resource Centre, accessible only to logged-in CRM users.

Data Stream Integration

Data streams, such as Kafka or Event Hubs, are recommended for medium to large organisations and B2B suppliers handling high data volumes. This method of integration offers virtually unlimited scalability, making it ideal for businesses requiring a robust and future-proof solution.

Beyond scalability, data stream integration is also the preferred approach for achieving a fully-fledged real-time integration, ensuring seamless and immediate data processing.

Queue-Based Integration

Queue-based integration solutions, such as Amazon SQS, Azure Service Bus, and similar message queue services, provide a reliable and scalable way to handle asynchronous data processing. These solutions ensure message durability, fault tolerance, and load balancing, making them ideal for event-driven architectures and systems requiring guaranteed message delivery. While queues are a strong option for many use cases, alternative integration methods can be explored based on specific business requirements on a case-by-case basis.

API-Based Integration (pull)

API-based integration enables the CRM to fetch data via REST or GraphQL APIs, allowing businesses to leverage existing web services for seamless data extraction. This method of integration is recommended for small to medium sized organisations who do not have the technical capacity to conduct an integration in-house and who already operate existing internal APIs.

Hybrid API Integration

A combination of push API and pull API can be utilized to achieve real-time data retrieval for critical events while leveraging existing APIs for other datasets. This hybrid approach ensures timely updates for key activities while maintaining efficiency for less time-sensitive data.

Real-time data is recommended for the following events:

• Player logins
• Registrations
• Deposits
• Withdrawals
• Rewards

Supported API Types

• REST APIs (JSON, XML support)
• GraphQL APIs

Key Benefits

• Scheduled and predictable data extraction
• Supports any data formats
• Allows integration with multiple third-party platforms

Integration Process

1. Access – API keys, documentation and credentials are to be supplied to Beintel.ai.
2. ETL – Data extraction, transformation and loading of data into the CRM data storage (including historical data up to 6 months of data).
3. Scheduling & Automation – Data retrieval API calls for periodic updates.

Security Considerations

• Token-based authentication
• IP whitelisting
• Data encryption during transmission

The CRM provides robust and flexible integration options, including direct database connections, API-based integrations, data streams and queue-based integrations. Each method ensures secure and optimised data access, catering to different business needs and operational environments. Choosing the right integration method depends on factors such as data volume, frequency of updates, and resource availability.