Models in production
From feature stores to inference — systems that train, deploy, monitor, and retire models responsibly.
Typical deliverables
- MLOps pipelines and registries
- Monitoring, drift, and evaluation
- GPU, batch, and vector inference patterns
- Responsible AI and governance hooks