Provides hardware-isolated, sub-60ms, ultra-low-overhead sandboxes to run untrusted LLM/agent code. Offers event-level snapshots, kernel-level egress control, credential vaulting, and drop-in E2B SDK compatibility for high-density AI agent deployment.
[next-mdx-remote-client] error compiling MDX: Unexpected character `5` (U+0035) before name, expected a character that can start a name, such as a letter, `$`, or `_` More information: https://mdxjs.com/docs/troubleshooting-mdx
Orchestrates stateful, long-running agent workflows as explicit graphs, with support for resuming execution, human review, and persistent memory. Best suited to applications that need control over workflow behavior; simpler linear tasks may call for a lighter approach.
Runs and serves language models locally on Apple Silicon and GPUs using native Metal, CUDA, and other backends. Its Zig engine performs inference without requiring Python or MLX.
