Notebooks.
Managed notebooks wired to the data platform and GPU compute for exploration and analysis.
Managed, collaborative notebooks with one-click GPU compute and direct access to the data platform — for exploration, analysis and prototyping without environment yak-shaving.
- Category
- AI & ML
- Deployment
- Managed → air-gapped
- Governance
- IAM · encryption · audit
Three steps to running.
Managed, collaborative, with reproducible environments.
One-click GPUs and direct access to the data platform.
Turn a notebook into a scheduled job in a click.
Notebooks, in full.
Attach and detach accelerators without leaving the notebook.
Direct, governed access to the lake, warehouse and vector store.
Share, comment and co-edit with reproducible environments.
Promote a notebook to a scheduled job in a click.
Provision it in a few lines.
Every service is reachable from the same SDK, CLI and infrastructure-as-code — one identity, one bill, one audit trail across the whole catalog.
import { aether } from "@aether/sdk";
// Notebooks on Aether Cloud
const res = await aether.ai.notebooks({
model: "aether-40b",
input,
stream: true,
});
for await (const token of res) process.stdout.write(token);At a glance.
- Compute
- One-click GPUs
- Data
- Lake · warehouse · vector
- Collaboration
- Share + co-edit
- Environments
- Reproducible
- Scheduling
- Promote to job
Built for real work.
Data exploration
Model prototyping
Reproducible analyses
On one model, not stitched together.
The usual stack runs notebooks in one product, the model in another and the data in a third — and the seams between them are the cost. Aether Cloud runs it on the same platform that serves the model, governs your identity and deploys into your boundary, with the rest of the catalog one hop away.
No stitching a vector DB to one place, a warehouse to another and a model to a third — notebooks sits next to the rest of the catalog, one identity, one bill.
The provider that runs Aether runs your notebooks — so the data and the model never leave the same governed boundary to talk to each other.
Need a capability that isn’t here yet? The model writes and deploys it into the same boundary — the catalog is a starting point, not a ceiling.
Good to know.
Managed notebooks with one-click GPUs and governed data access — next to the model and training clusters.
Yes — promote it to a scheduled, reproducible job in a click.
Yes — direct but governed access to the lake, warehouse and vector store.
Your boundary, your choice.
Pairs well with.
The simulation-native foundation model itself, served as an API — the core every other service builds on.
Low-latency, streaming inference for every model size, with pinned versions and structured output.
Pre-wired multi-node GPU clusters with scheduling, checkpointing and fault tolerance.
Customer-controlled fine-tuning and adapters on data that never leaves your boundary, with eval gates.
Model and prompt registry, evals, deployment and drift monitoring — versioned and auditable.
Build a working app, agent or simulation by describing it, deployable in a click. See Aether Studio.
Run Notebooks on Aether Cloud.
Managed notebooks wired to the data platform and GPU compute for exploration and analysis. Deployable managed, in your VPC, on-prem or fully air-gapped — talk to us about the configuration your workloads and your boundary require.