Interests: AI Infrastructure
Cyril Bandolo is a cloud and AI architect focused on building production-grade ML and GenAI systems on AWS. His work centers on turning ambiguous business problems into secure, observable, and practical architectures, with experience spanning event-driven platforms, real-time ML inference, retrieval-augmented generation (RAG), and agentic workflows.
He is especially interested in the parts of AI systems that matter after the demo: retrieval quality, evaluation, guardrails, cost control, and operational resilience. Across his projects, Cyril has worked on systems for intelligent triage, security automation, internal AI platforms, and grounded question-answering, with an emphasis on explainability, governance, and measurable business value.
Cyril enjoys exploring how cloud-native design, strong engineering discipline, and clear architectural tradeoffs can make AI systems more trustworthy and useful in practice. He writes and speaks about AWS-native AI architecture, RAG quality, and the realities of moving ML and GenAI systems from prototype to production.
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