AI Infrastructure
Storage designed for datasets, checkpoints and embeddings.
Throughput-oriented storage for training data, model artefacts, vector indexes and retrieval corpora.
GPU workloads
MockInference · production74%
Fine-tuning job91%
Notebook · research36%
Endpoints online5 / 5
VRAM allocated148 GB
Capabilities
What AI Storage includes
Dataset storage
Parallel-read storage for training and evaluation datasets.
Artefact registry
Versioned storage for checkpoints and model artefacts.
Vector workloads
Storage patterns for embeddings and retrieval indexes.
Lifecycle policies
Retention and archival policies per project.
FAQ
Common questions
What do you want to build?
Tell us about your website, application, cloud or AI workload. Our team will recommend the right infrastructure and managed-service model.