Skip to content
Close
LOGIN
SEARCH
Contact
Contact

Run inference and agents in production.

From serverless endpoints to dedicated, stateful compute —
Aurora AI Cloud serves models, holds state, and runs the agents that orchestrate them.

Start in Console
Talk to Sales

Serverless to Dedicated Inference

Start serverless, scale into dedicated GPU endpoints as traffic grows — no re-architecture.

  • OpenAI-compatible API — drop-in endpoints for open-weight LLM and multimodal models.

  • Autoscaling & batching — latency-aware scheduling and scale-to-zero; pay for what you serve.

  • Performance economics — maximum tokens-per-dollar, predictable latency under load.

Stateful Inference for Agents

Sessions hold their state across requests, so agents advance on new tokens — not the whole context each turn.

  • State across requests — sessions persist instead of resetting every call.
  • Lower latency at depth — avoids costly re-prefill as context grows.
  • Storage-backed memory — checkpoints and outputs land on Aurora AI Storage.

Dedicated CPU & VMs

Infrastructure for agents, not just models — persistent compute, background workers, and a safe place to run code, beside the GPUs.

  • Dedicated CPUs via VMs — background workers, tool calls, and orchestration.
  • Persistent sandboxes — workspaces that hold state across sessions.
  • CPU + GPU together — agents run on CPU and call models on GPU, one network.

Fine
Tuning

Adapt open-weight models to your data

Managed
Orchestration

Scale and route workloads automatically.

Monitoring
& SLA

24×7 monitoring, 99.9% uptime SLA.

Digital rendering of Aurora Infra Private AI containerized data center

Deploy models. Run agents. Scale automatically.

Talk to an Expert
Start in Console