Computers
for Agents
Daytona is the secure and elastic cloud infrastructure built for autonomous agents.
Agents at these companies use Daytona
Meta
Cohere
Sambanova
Writer
Long Lake
Turing
Bespoke Labs
Rillet
Martian
Clay
Agents don't use computers the way people do. Daytona rebuilds the compute layer around how they actually work.
Instant by default
Under 100 ms from API call to running machine — as cheap as calling a function.
Safe to run blind
Code nobody reviewed runs in a sandbox that contains it — not your infrastructure, data, or users.
Free while stopped
Per-second billing, only while running. Stopped sandboxes keep their state and cost next to nothing.
Machine Speed Infrastructure
Sub-100ms environment creation means zero bottlenecks between agent reasoning and execution, enabling real-time autonomous workflows that compound at machine speed.
Instantaneous Elasticity
Massive parallelization without infrastructure complexity. Spin up isolated agent workloads on-demand with complete isolation, secure credential handling, and the same sub-100ms performance—whether you're running one agent or orchestrating thousands.
Agent Native Architecture
From headless containers to full desktop environments, Daytona provides complete computing flexibility. Your agents can execute code, browse the web, manipulate files, and use any tool—across Linux, Windows, or macOS—all through the same unified infrastructure.
Fork a running sandbox — filesystem and memory — into a fully independent copy. Branch an agent's world mid-run and test different paths in parallel.
Tail Error Rates at Scale
Run a million trajectories and a 0.1% failure rate breaks 1,000 of them. Daytona holds a 0% error rate out to P99.99 of sandbox starts.
Improving Agent Performance
Daytona sandboxes cold-start in 162ms — up to 110× faster than cloud VMs. Over a million trajectories, that's a 5,316 worker-hour gap. Read the paper
Case Studies
Hundreds of thousands of sandboxes a month. Sub-100ms starts under real load. Engineering teams reclaimed from infrastructure. Here is what it looks like when agents run on Daytona in production.
“One thing that Daytona does incredibly well is its sandbox provisioning times. When you're provisioning tens of thousands of sandboxes, those milliseconds add up.”
- 200
- Hours saved per week on sandbox infrastructure
- 6
- Months of engineering time saved
- 100ms
- Or less to provision a sandbox
Every agent workload. One compute layer.
Pick a workload and start from a working example. Every solution links to a step-by-step guide.
+20 more
All Guides
- Read the Claude Code guide
Coding agents.
Run Claude Code, Codex or your own agent in an isolated sandbox: it edits files, runs commands and streams its logs back.
- Read the OpenCode guide
Parallel sessions.
Give every agent session its own isolated sandbox, so parallel runs never step on each other.
- Read the RL guide
Reinforcement learning.
Spin up hundreds of parallel sandboxes as a coding environment, grade every rollout and train on the results.
- Read the OpenClaw guide
Always-on assistants.
Keep a personal AI assistant online 24/7 in an isolated sandbox, connected to Telegram and WhatsApp.
Built for autonomy. Certified for the enterprise.
Every sandbox runs on dedicated, isolated infrastructure — no shared compute, no cross-tenant risk. SOC 2 and GDPR come standard. Enterprise adds HIPAA, SSO, audit logs, and BYOC, so Daytona can run in your own cloud.
FAQ
Extra questions about the how and the why? Reach out on our community Slack and we’ll happily expand.
Daytona gives AI agents secure, elastic computers where they can execute code, use tools, preserve state, and return results without sharing a host environment.
Each workload runs in an isolated sandbox with controlled networking, filesystem boundaries, and lifecycle controls so untrusted code can be inspected and contained.
AI sandboxes are short- or long-lived compute environments for agents. They make tool use repeatable by giving every run its own machine, files, dependencies, and execution history.
Use the API, SDKs, or CLI to create sandboxes from your agent runtime, connect tools, stream execution results, and tear environments down when the work is done.
Daytona combines sandbox isolation, policyable access, audit-friendly execution, and deployment controls so teams can move agent workloads toward production with fewer bespoke guardrails.
Daytona covers the compute layer behind agents: creating sandboxes, running generated code, managing state, and scaling execution across development and production workloads.