Accelerated computing
Physical AI, at the plant edge
Lines fill tens of thousands of containers an hour, so perception has to be local and fast. Brewira runs GPU inference at the line edge and keeps training, simulation and optimization in the cloud, in a private cloud or on-prem. Items marked planned are on the roadmap, not running.
Jetson Orin / Thor · DeepStream · TensorRT · Holoscan
Edge perception
8 to 24 camera feeds per line through DeepStream pipelines and TensorRT detectors, segmentation, OCR and fill-level models; Holoscan synchronizes cameras with gravity, CO2 and clarity analyzers and filler and pasteurizer telemetry. Design target: sub-100 ms reject decisions.
Triton · NIM
Model serving
Vision, time-series, anomaly, process and food-safety reasoning models behind one orchestrator, with version routing by brand, package and line. Design target: 20 to 60 model versions per enterprise tenant.
DGX / HGX · NeMo
Training (planned)
Line vision, time-series forecasters, anomaly models and NeMo-based beverage reasoning fine-tuned from labeled batch outcomes, brewmaster corrections, lab results and release decisions. Design target: weekly retraining for wedge models, monthly for validated process models.
Omniverse · Modulus · OVX
Digital twin (planned)
The Cuvera as-produced line twin: CUDA-accelerated fermentation, carbonation, mixing and pasteurization heat simulation run before the batch, for new SKU setup and batch planning when a trial is expensive.
Cosmos · Omniverse Replicator
Synthetic data (planned)
Rare leaker, low-fill, overfill, cap-skew, seam, label-shift, condensation, glare and foreign-body scenarios generated with domain randomization and validated against real plant events before use.
cuOpt
Optimization
Brew and fill schedules, changeovers, CIP cycles, water and energy allocation and takt balancing under line, tank, product and sanitation constraints, recomputed on the GPU when the plant is disrupted.
RAPIDS
Data engineering
Image, time-series and batch-genealogy ETL for feature generation, quality correlation and cross-plant benchmarks on the GPU.
Isaac · Jetson
Robotic handling
Pack, case and palletizing handling, with perception and motion policies built and validated in simulation before they move a pallet.