Over the past few weeks, I’ve been experimenting with a question that kept coming to mind while watching Formula 1: Could a local AI system act like a race engineer and make real-time strategy calls from live telemetry? That idea eventually turned into a fully local AI pit-wall prototype capable of: Streaming telemetry at 10Hz Predicting tire cliff drop-offs one lap early Retrieving historical race knowledge using RAG Generating radio-style strategy calls with a local LLM Producing automated post-race PDF reports And the entire stack runs offline. The Goal Most AI systems today rely heavily on cloud inference. I wanted to explore something different: low-latency local inference explainable predictions real-time telemetry processing The project combines sequential ML prediction with retrieval-augmented contextual reasoning in a motorsport-inspired environment.…