Shelter41
Infrastructure platform for running long-running AI coding agents in persistent, pausable cloud sandboxes with orchestration, observability and governance.
At a Glance
Engagement
Available On
Listed Oct 2026
About Shelter41
Shelter41 provides infrastructure for long-running AI agents. It offers persistent cloud workspaces for coding agents such as Claude Code and Codex, with browser, CLI and SDK access, and enterprise options that are managed by Shelter41 or run on a customer's own Kubernetes cluster.
What It Is
Shelter41 is an agent orchestration and workspace platform. A user describes a task, such as building, testing and reviewing a sign-in flow, and an orchestrator chooses agents, allocates an isolated sandbox for each, and pauses or resumes compute as work proceeds. The site's example sequence is labeled illustrative.
Persistent Workspaces and Idle Compute
Shelter41 separates an agent's identity, session history and workspace memory from its compute. Compatible sandboxes sleep automatically after a configurable idle delay, including supported waits for user input, and wake when new work arrives. Pausing keeps files and the running environment; parking removes compute while retaining agent identity and recorded history. Agents in one workspace can share project observations through workspace memory, while each runs in its own sandbox. Per the FAQ, recovering a native conversation after a sandbox is destroyed depends on the harness, and the documented path currently covers Claude Code.
Control, Observability and Governance
The platform's control view tracks running, waiting and paused agents. Observability covers run reliability, performance, token usage and cost by runtime, filterable by workspace, runtime, agent or user. Governance covers organization roles, per-member access to runtime credentials, and trace and tool-payload capture settings. A skills library lets teams install skills on compatible agents. The dashboard figures shown are sample data.
Integrations and Deployment
Listed integrations include GitHub, GitLab, Linear and Supabase via MCP, plus the sh41 CLI. Slack, WhatsApp and Telegram are marked coming soon. The FAQ says the built-in harness catalog includes Claude Code, Codex, Kimi Code and experimental Grok Build; other harnesses shown illustrate the broader concept. Enterprise customers can choose a managed deployment or run on their existing Kubernetes infrastructure; fully offline requirements need separate review.
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Pricing
Pay As You Go
Hosted pay-as-you-go with prepaid credits that never expire; no subscription or seat fees. First signup includes 6h of raw Agentic Compute.
- Start with $20 in credits
- Up to 10 team members
- 20 workspaces for your projects
- Up to 10 agents running simultaneously
- Persistent agent conversations and shared workspace memory
- Team roles and access controls
- Web, CLI, and API access
- Supported GitHub, GitLab, and coding-agent integrations
- Standard agent compute (4 vCPU, 4 GiB RAM): $0.50 per running agent-hour
- 1 GiB snapshot and attachment storage included per organization
- Additional retained storage: $0.10 per GiB per 30 days
- Starting balances: $20 = 40 agent-hours, $60 = 120 agent-hours, $200 = 400 agent-hours
- AI-provider subscriptions and model usage billed separately by your provider
Enterprise
Managed by Shelter41 or fully on-premises on your Kubernetes infrastructure, with custom pricing.
- Managed by Shelter41 or fully on-premises
- Persistent agent workspaces and context
- Custom workspace and concurrent-agent limits
- Architecture review and deployment planning
- Tailored onboarding and contracted support
- Custom agreement and invoicing
Capabilities
Key Features
- Agent orchestration across multiple coding agents
- Isolated sandbox per agent
- Automatic sandbox pause and resume with files and context retained
- Persistent workspaces with shared project memory
- Observability of runs, token usage and cost
- Governance of roles, runtime credentials and trace capture
- Shared skills library for compatible agents
- sh41 CLI and SDK
- Managed or on-premises Kubernetes enterprise deployment