Research
Notebook-first workflows
A governed machine-learning engineering surface for research, training, inference, evaluation, and deployment across the Swarmie empire.
Best for teams that need PyTorch, TensorFlow, JAX, OpenAI SDK, Hugging Face, Azure ML, and Vertex AI in one coherent workflow.
| Layer | What it does | Why it matters |
|---|---|---|
| Frameworks | PyTorch, TensorFlow, and JAX for training and experimentation | Supports modern ML workloads |
| Providers | OpenAI SDK, Hugging Face, Azure ML, and Google Vertex AI | Keeps cloud and model options flexible |
| Ops | Validation, evaluation, registry, monitoring, and rollback | Makes ML production-safe |
Notebooks, datasets, and baseline experiments.
Training jobs, evaluation, and inference endpoints.
RAG, agents, monitoring, and governed deployment.
Dedicated compute, security review, and rollout support.
Research, data, training, and deployment in one system.
OpenAI, Hugging Face, Azure, and Vertex without lock-in.
Drift, security, evaluation, and rollback built in.