Tensorlake

Hosted sandboxes and versioned filesystems for running and evaluating AI agents

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About Tensorlake

Tensorlake provides isolated sandboxes and versioned filesystems for deploying, running, and evaluating AI agents. It offers persistent or ephemeral Linux environments with their own filesystems, shells, packages, and processes, running inside secure microVMs. Agents can compile code, run databases, process large files, or execute tool calls in isolation from the harness. Sandboxes sleep on inactivity and wake instantly, supporting sessions that run for hours or days. The platform includes a versioned filesystem that mounts like a POSIX directory, automatically replicating settled writes to durable storage and allowing snapshots for time travel or sharing. It also provides managed Git repositories that scale to millions of repos, supporting plain Git operations or mounting branches without cloning. Tensorlake is designed for teams building agentic solutions, offering tools for running RL rollouts, evaluations, and CI pipelines that scale with agent workloads.

Key features

Persistent and ephemeral sandboxes
Versioned filesystem with POSIX mounts and autosave
Managed Git with server-side merges and branch promotion
Secure microVM execution for tool calls
Sandbox lifecycle control (suspend, resume, fork)
Cross-platform filesystem mounts (Linux, macOS)
RL rollouts and evaluation environments
CI pipelines for agent deployments

Use cases

Running agent harnesses and tool calls in isolation
Building versioned datasets and model outputs
Executing RL rollouts and evaluations at scale

Pros

Isolated Linux sandboxes with dedicated filesystems and processes
Versioned filesystem with automatic snapshots and time-travel capabilities
Managed Git repositories with server-side merges and branch promotion
Persistent or ephemeral sandboxes with configurable resources
Supports compiling code, running databases, and processing large files

Cons

No free tier beyond developer sandbox
Pricing based on usage credits with no postpaid option
Limited to Linux-based environments
Requires prepaid credits for production workloads

Frequently asked questions about Tensorlake

What is Tensorlake and what does it do?

Who is Tensorlake designed for?

Tensorlake is designed for teams building agentic solutions, such as those working on AI agents, reinforcement learning rollouts, evaluations, and CI pipelines that scale with agent workloads.

How do I get started with Tensorlake?

You can get started with Tensorlake by creating a sandbox using the CLI or SDK, importing the Tensorlake library, and running commands or code within the isolated environment. Documentation and examples are available to guide the setup process.

Can Tensorlake integrate with existing tools and workflows?

Yes, Tensorlake supports plain Git operations and can mount repositories without cloning, allowing integration with existing Git workflows. It also provides POSIX directory mounts for seamless interaction with local or cloud environments.

What are the key features of Tensorlake's versioned filesystem?

The versioned filesystem in Tensorlake mounts like a POSIX directory, automatically replicates settled writes to durable storage, and allows snapshots for time travel or sharing. It supports suspending, resuming, and copying entire sandboxes.

How does Tensorlake handle security for agent tool calls?

Tensorlake executes LLM-generated code inside secure microVMs, isolating tool calls from the harness to ensure safety and prevent interference with the host environment.