End-to-End Lifecycle Management

Provide comprehensive management capabilities throughout the entire lifecycle of language models, including data preparation, model training, deployment, and monitoring

Kubernetes Native

Designed and built using native Kubernetes features, including OIDC, RBAC, Operator, multi-tenant etc ..., can seamlessly integrate with existing Kubernetes clusters and infrastructure

Versioning and Experiment Tracking

Allow experiments and evaluations, enables reproducibility, comparison of different model versions, and efficient collaboration among team members.

Monitoring and Logging

Robust monitoring and logging functionalities, allowing users to track model performance, resource utilization, and other relevant metrics

Automation and Orchestration

Provide automation and orchestration capabilities, streamlining the end-to-end workflow of language model development and deployment