Inference at the edge. Air-gap ready.
On-premise inference on Jetson AGX Orin — no cloud dependency, no data leaving the site. TensorRT-optimized models, quantized for edge hardware, with OTA updates through staged canary rollout and automatic rollback.
Edge deployment
Capabilities
Full autonomy stack on a single board.
TensorRT Optimization
Post-training quantization with layer sensitivity analysis. ONNX export with numerical verification. Models optimized for Jetson AGX Orin compute budget.
Triton Inference Server
Multi-model serving on edge hardware via Triton gRPC. ModelControl API for hot-swapping models and LoRA adapter variants without restart.
Edge LLM
TensorRT-LLM for on-device language model inference. llama.cpp fallback for constrained hardware. AWQ quantization for minimal quality loss at 4-bit.
OTA Model Updates
MLflow webhook triggers OTA bundle creation. Staged canary rollout — deploy to 5% of fleet, validate metrics, expand or auto-rollback.
Air-Gap Deployment
Full offline operation. Models, configs, and runtime packaged for disconnected environments. Sync when connectivity is available.
Drift Monitoring
Evidently drift detection on edge. Active learning via LanceDB uncertainty-diversity ranking identifies high-value data for model improvement.
No cloud required.
Run inference on-site with full air-gap capability. Your data stays on your network. Models update through staged canary rollout.