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Understanding best practices for building custom AI-powered automation using Oracle AI Services

Hello everyone,

I’m currently exploring Oracle AI Services and looking to understand best practices for building AI-powered automation workflows, especially when integrating AI models with backend services and cloud infrastructure.

My main areas of interest include:

  • Using Oracle AI Services with REST APIs for automation
  • Integrating AI models with cloud-native applications
  • Processing structured and unstructured data using Oracle AI
  • Designing scalable architectures using Oracle Cloud Infrastructure (OCI)

I would like to know how developers typically structure their architecture when combining Oracle AI Services with backend systems (for example, using microservices, event-driven architecture, or serverless functions).

Additionally, I’m interested in learning:

  • Recommended architecture patterns
  • Best practices for performance and scalability
  • Real-world use cases or examples
  • Common pitfalls to avoid

I’m currently learning and experimenting with AI-driven tools and cloud infrastructure, and I’m eager to deepen my understanding of Oracle’s AI ecosystem.

Thank you in advance for any guidance or recommendations.

Best regards,
Bangkah

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Added on Feb 13 2026
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