Predictive systems for large-scale computing.
Hardware telemetry, failure prediction, anomaly detection, LLM workflows, retrieval, monitoring, and MLOps.
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Sai Karan Reddy
Work
This collection brings together production work and independent builds. The settings are different, but the rhythm is the same: understand the problem, build with care, reflect honestly, and leave room for the next question.
Industry
Hardware telemetry, failure prediction, anomaly detection, LLM workflows, retrieval, monitoring, and MLOps.
Read the full story ↗Credit risk, AML, graph features, explainability, cloud deployment, and model governance.
Read the full story ↗Curious Builds
Can a machine begin to understand expression through 68 small observations?
Read project ↗How can a prediction support an earlier, better-informed decision?
Read project ↗What can many individual experiences reveal about one place?
Read project ↗Can a question grow into shared learning through conversation?
Read project ↗How do separate technical parts become one dependable user journey?
Read project ↗How do weather patterns become clearer when viewed across time and scale?
Read project ↗What makes data dependable before it reaches the people using it?
Read project ↗Every project here answered one question.