In this session, attendees will explore the end-to-end journey of building and scaling an AI-powered platform serving paying customers with AI integrations. We’ll cover: Architectural Foundations: Designing a microservices-based core with cloud deployments for scalability. Scalability and Resilience: Leveraging auto-scaling groups, container orchestration, and managed database services to ensure high availability under variable load. LLM Integration: LLM support, conversations, messages, attachments, and memory imitation with large context windows. Best Practices and Lessons Learned: Challenges faced—such as cold starts, latency tuning, and data privacy—and how they were overcome