Compile code, run databases, process 5GB files. Real-time cloning to fork a sandbox into multiple copies all the same state.
The data plane deploys directly in your cloud. Data doesn't leave your network. You use your own reserved instances and pricing.
Spin up 200 sandboxes per second. Run 100K at once. Cold start under a second.
Sandboxes spread across AWS, GCP, Hetzner, or bare metal automatically. Consistent CPU bundles across the fleet so RL training runs don't get variance from mismatched hardware.
Full state preserved on suspension or crash. Resume where you left off, debug what happened, or fork into a new sandbox. Auto-suspend watches memory access so you only pay when something is actually running.
Cluster Scheduler Designed for Sandbox Orchestration
We built a state of the art cluster scheduler designed to handle high throughput sandbox creation at scale with consistent latency
A copy on write state machine in the scheduler enables low latency placement decisions for millions of sandboxes in minutes
The scheduler enables oversubscribing resources so you can pack more sandboxes on dedicated clusters
Sandboxes are allocated resources dynamically without incurring scheduling overhead
The dataplane of the scheduler uses a driver interface to enable resource isolation using Firecracker and CloudHypervisor based on workload charactaristics
Built for workloads that hit disks
Bring Tensorlake Into Your Cloud
Run sandboxes and applications in your own cloud or private environment when you need lower egress, stricter network boundaries, dedicated capacity, or more predictable performance.
Keep code and data inside your preferred cloud boundary when shared SaaS deployment is no longer acceptable.
Keep compute closer to your data and tighten the runtime behavior for latency-sensitive agent workloads.
Move from usage-based hosted infrastructure to capacity you can plan, reserve, and operate more predictably.
Tensorlake is the Agentic Compute Runtime the durable serverless platform that runs Agents at scale.
