Solutions

Sandboxes built for
agents, LLMs & RL.

AvLabs is the execution layer AI systems need — isolated, disposable machines your code can create, drive, and destroy programmatically. No VMs to manage. No residue left behind.

lifecycle
01 create POST /sandboxes
02 run agent · llm · rl
03 destroy zero residue
01 agents

Coding agents

Give your agent a real machine — install packages, edit files, run tests, iterate. Isolated from your infra, destroyed when the loop ends.

  • Full root shell
  • Custom images & deps
  • Stream stdout / files
02 llms

LLM code execution

Run model-generated code safely. Every tool call gets a fresh sandbox — no shared state, no escape to your host.

  • Untrusted code isolation
  • Language-agnostic runtimes
  • Second-level billing
03 rl

RL rollouts

Spin up thousands of concurrent environments for training and eval. Ephemeral worlds that boot fast and scale with your GPU jobs.

  • Massive parallelism
  • Reproducible envs
  • Pay only while alive
04 async

Background agents

Long-running workers with the tools, context, and credentials already in place — a full dev environment your agent owns.

  • Persistent workspaces
  • API-driven lifecycle
  • Zero babysitting
05 evals

Evals & benchmarks

Identical sandboxes for every trial. Snapshot state, fan out parallel runs, score agents without flaky local setups.

  • Deterministic starts
  • Parallel fan-out
  • Clean teardown
06 ci

CI & batch jobs

A fresh machine per job. Boots in about a second, bills by the second, leaves zero residue when the job exits.

  • One job → one box
  • Any runtime image
  • Destroy on exit

One API. Any workload that needs a machine. Create → run → destroy.

read the docs