I built a pipeline for querying fleet telemetry (AVs, robots, vehicles) in natural language. Load Parquet or CSV into cuDF, then ask things like "Which vehicles exceeded 120 km/h in region X?" and get back IDs and metrics.
Tech: cuDF for GPU ingest/analytics, NVIDIA NIM on GKE for LLM inference, format-aware model selection (GGUF local, TensorRT prod). Three notebooks: data ingest with pandas vs cuDF vs cudf.pandas benchmarks, local Gemma 2 inference, and full NIM deployment. Runs on Colab with a T4 for notebooks 1 and 2; notebook 3 uses GCP and NIM on GKE.
Show HN: H.e.i.m.d.a.l.l – Telemetry-to-insight pipeline for fleet telemetry | Heykuki News