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KadirGokdeniz/README.md

Kadir Gökdeniz

ML/AI engineer, mostly on aviation — clear-air-turbulence forecasting and LLM/agent systems for airline operations. I care more about the part after the demo: monitoring, failover, and keeping things running under real load.

MS in AI at CU Boulder. More at kadirgokdeniz.com.

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  1. global_gate global_gate Public

    Voice-enabled, bilingual RAG system for airline policy questions — live demo, built with production-grade practices (Prometheus monitoring, dual-LLM failover, chaos-tested).

    Python

  2. AeroCAT-ML AeroCAT-ML Public

    Machine Learning-Driven Clear Air Turbulence Prediction for Operational Aviation Safety

  3. ActionFlow ActionFlow Public

    Multi-agent LLM system for travel support that autonomously understands intent and executes actions across web, WhatsApp, and voice channels.

    Python

  4. layover layover Public

    Voice interpreter for airline ground ops that keeps flight codes, gates, and times intact across translation.

    TypeScript