tensorlakeai/tensorlake

What it solves

Tensorlake provides a secure, high-performance compute infrastructure for AI agents. It solves the problem of safely executing untrusted, LLM-generated code and managing the state of agentic applications at scale without sacrificing speed or security.

How it works

Tensorlake uses Firecracker MicroVMs to create isolated sandboxes that act as execution environments for agents. These sandboxes are managed by a dynamic cluster scheduler called Lattice, which allows them to start in under a second. The platform includes a serverless function runtime for orchestration, allowing developers to build complex agentic workflows with fan-out capabilities. It also features Cloud Volumes for durable, versioned file management and a system for snapshotting and cloning sandbox states (including memory and filesystem) to create durable memory for agents.

Who it’s for

It is designed for developers building AI agents that require a secure environment to run tools, execute Python code, or maintain long-term state across sessions.

Highlights

• High-Performance I/O: Achieves near-SSD speeds for filesystem operations, outperforming several competitors in SQLite benchmarks.
• Instant Scaling: Supports up to 5 million sandboxes per project with sub-second startup times.
• State Management: Supports snapshots, cloning, and auto suspend/resume to preserve agent memory and filesystem state.
• Secure Isolation: Uses hardware-virtualized MicroVMs to isolate untrusted code from the rest of the infrastructure.
• Serverless Orchestration: Provides a distributed runtime to deploy agentic applications as scalable functions.