We design the foundational MLOps infrastructure that lets your data science team move from notebooks to production with confidence. Our architectures include everything from feature stores and model registries to serving layers and monitoring — all integrated into your existing engineering workflows.
What's Included
Feature store design with Feast or Tecton
Model serving with TensorFlow Serving, Triton, or vLLM
Experiment tracking and model registry (MLflow, W&B)
CI/CD pipelines for model training and deployment
GPU cluster management and cost optimization
Model monitoring, drift detection, and automated rollback