Stateful Sandboxes Compute for Agents

Run agents and tool calls in isolated sandboxes, keep state between runs, wake them on demand, and give them the real software stack they need to do useful work.

LIVE MIGRATION
MEDIAN STARTUP TIME:150ms
STATEFUL BY DEFAULT
DYNAMIC RESOURCE ALLOCATION
Sandboxes for Agent Harnesses

Sandboxes for Running Agent Harnesses

Run the agent itself inside an isolated, stateful computer instead of on the app server. This is the sandbox mode for browsing agents, research harnesses, and long-running sessions that need files, bash, packages, and working state.

ingredients
Isolated runtime for the harness

Give the agent its own filesystem, shell, packages, and processes instead of sharing the app server runtime.

Stateful by default

Sandbox sleeps on inactivity, wakes instantly when invoked

Built for long-running sessions

Near-SSD speed in a VM, 2x faster than Vercel, 5x faster than E2B

Real software stacks

Near-SSD speed in a VM, 2x faster than Vercel, 5x faster than E2B

visual 1.1
tensorlake
never lose progress
visual 1.1
tensorlake
never lose progress
visual 1.1
tensorlake
never lose progress
visual 1.1
tensorlake
never lose progress
visual 1.1
tensorlake
never lose progress
THE SOLUTION
TL LABS
BUILD FURTHER WITH SERVER-LESS
THE SOLUTION
TL LABS
BUILD FURTHER WITH SERVER-LESS
THE SOLUTION
TL LABS
BUILD FURTHER WITH SERVER-LESS
THE SOLUTION
TL LABS
BUILD FURTHER WITH SERVER-LESS
Tool Sandboxes

Isolated Execution Environments for Running Tools

Keep the agent harness outside the sandbox and create isolated sandboxes only when a tool needs risky or heavy execution. This is the pattern for code interpreters, browser helpers, and tool-calling agents that should not run untrusted code inside the harness itself.

ingredients
Run LLM-generated code away from the harness

Execute code, browsers, or system tasks in a separate sandbox so the main agent never shares its runtime.

Control the network per sandbox

Predictable throughput means fresh sessions spin up immediately, even when a thousand others are mid-task.

Size sandboxes dynamically at runtime

Run generated code safely. LLMs write code to compute answers, transform data, query databases. Every session gets its own sandbox so untrusted code can't touch system integrity or leak data across sessions.

Other Sandbox Patterns

Infrastructure for RL Environments

PREPARE ONCE, CLONE MANY

Snapshot a prepared environment and reuse it across workers.

KNOWN STARTING STATE

Keep files, packages, processes, and seeds consistent across runs.

SCALE ROLLOUTS AND EVALS

Snapshot a prepared environment and reuse it across workers.

DYNAMIC RESOURCE ALLOCATION

Choose the CPU, memory, GPU, and image each environment needs.

Benchmark setup: 2 vCPU / ~4 GB sandboxes, 3 runs.

Built for workloads that hit disks

In our published SQLite benchmark across Tensorlake, Vercel, E2B, Daytona, and Modal, Tensorlake was the fastest across default, fsync, and large-dataset runs.
FASTEST IN DEFAULT
FASTEST IN SYNC
FASTEST IN LARGE
ORCHESTRATION

Sandbox-Native Orchestration for Agents

Once sandbox usage turns into a real application, Orchestrate is the layer that coordinates it. This is where you add application endpoints, durability, fan-out, retries, and application-level observability on top of sandbox execution.

ingredients
Application endpoints

Expose sandbox-backed workflows as callable applications instead of stitching together raw VM APIs.

Distributed fan-out

Predictable throughput means fresh sessions spin up immediately, even when a thousand others are mid-task.

Wake on request

Run generated code safely. LLMs write code to compute answers, transform data, query databases. Every session gets its own sandbox so untrusted code can't touch system integrity or leak data across sessions.

Application observability

Run generated code safely. LLMs write code to compute answers, transform data, query databases. Every session gets its own sandbox so untrusted code can't touch system integrity or leak data across sessions.

Queues, timers, and retries

Run generated code safely. LLMs write code to compute answers, transform data, query databases. Every session gets its own sandbox so untrusted code can't touch system integrity or leak data across sessions.

THE SOLUTION
TL LABS
BUILD FURTHER WITH SERVER-LESS
THE SOLUTION
TL LABS
BUILD FURTHER WITH SERVER-LESS
THE SOLUTION
TL LABS
BUILD FURTHER WITH SERVER-LESS
THE SOLUTION
TL LABS
BUILD FURTHER WITH SERVER-LESS
THE SOLUTION
TL LABS
BUILD FURTHER WITH SERVER-LESS
TRUSTED BY PRO DEVS GLOBALLY

Tensorlake is the Agentic Compute Runtime the durable serverless platform that runs Agents at scale.

“With Tensorlake, we've been able to handle complex document parsing and data formats that many other providers don't support natively, at a throughput that significantly improves our application's UX. Beyond the technology, the team's responsiveness stands out, they quickly iterate on our feedback and continuously expand the model's capabilities.”

Vincent Di Pietro
Founder, Novis AI

"At SIXT, we're building AI-powered experiences for millions of customers while managing the complexity of enterprise-scale data. TensorLake gives us the foundation we need—reliable document ingestion that runs securely in our VPC to power our generative AI initiatives."

Boyan Dimitrov
CTO, Sixt

“Tensorlake enabled us to avoid building and operating an in-house OCR pipeline by providing a robust, scalable OCR and document ingestion layer with excellent accuracy and feature coverage. Ongoing improvements to the platform, combined with strong technical support, make it a dependable foundation for our scientific document workflows.”

Yaroslav Sklabinskyi
Principal Software Engineer, Reliant AI

"For BindHQ customers, the integration with Tensorlake represents a shift from manual data handling to intelligent automation, helping insurance businesses operate with greater precision, and responsiveness across a variety of transactions"

Cristian Joe
CEO @ BindHQ

“Tensorlake let us ship faster and stay reliable from day one. Complex stateful AI workloads that used to require serious infra engineering are now just long-running functions. As we scale, that means we can stay lean—building product, not managing infrastructure.”

Arpan Bhattacharya
CEO, The Intelligent Search Company
CUSTOMER STORIES

Tensorlake built for world-class enterprises

FOR TEAMS OUTGROWING SAAS

Bring Tensorlake Into Your Cloud

BYOC is scale and control

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.

Security and network boundaries

Keep code and data inside your preferred cloud boundary when shared SaaS deployment is no longer acceptable.

Performance and latency control

Keep compute closer to your data and tighten the runtime behavior for latency-sensitive agent workloads.

Cost and reserved capacity

Move from usage-based hosted infrastructure to capacity you can plan, reserve, and operate more predictably.

SECURITY

Security Built for Agentic and AI Data Workflows

Tracing and Observability

Full traces of every function and tool call — with logs, timing, and structured execution paths.

Sandbox for tool calls

Tool calls run in isolated sandboxes, making them safe for LLM-generated code.

Sandbox for agent harness

Each agent harness executes inside an isolated sandbox to keep sessions safe and independent.

HIPAA / SOC2 Type2 Compliant

Secure by default for PHI, PII, and sensitive documents.

Isolated & Auditable Data Boundaries

Each project’s data lives in its own isolated bucket with full audit trails and strong RBAC controls.