AI development environments

A protected workspace for OpenHands

Name: Secure OpenHands Cloud Hosting
Brand: Seemi Cloud

Give an AI software-development agent access to an isolated Linux workspace and development tools, while placing the web interface behind Seemi forward authentication and retaining control of model-provider credentials.

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SEEMI CLOUD

Reliable infrastructure with operational safeguards built in

Secure by design Backup ready Regional choice API and agent ready

Capabilities

Designed for practical cloud operations

Agentic software workflows

Use OpenHands for coding, repository work, command-line tasks, file editing, testing, maintenance, and other software-engineering workflows.

Isolated Linux workspace

Run agent tools inside a dedicated containerized environment instead of granting access to the Seemi Cloud host.

Protected web interface

The OpenHands UI is placed behind Seemi forward authentication using Microsoft or Google SSO and resource authorization.

Bring your model provider

Customers subscribe to and configure their own supported AI model providers and remain responsible for model charges and credentials.

Persistent workspace backup

Protect configured persistent volumes using scheduled encrypted Restic snapshots.

Future platform integration

The roadmap includes model choices, token controls, application templates, image creation, and direct deployment into Seemi infrastructure.

Use cases

Built for real workloads

Choose a supported service from the catalog or bring a workload that fits your architecture.

AI-assisted coding

Repository maintenance

Agentic application prototyping

Automated development tasks

Secure browser-based agent access

Agentic development

Give coding agents a governed workspace

Run repository, terminal, file, and development workflows inside an isolated environment while controlling model credentials and protecting web access.

Model tokens are separate

Seemi Cloud does not currently resell AI model tokens. Customers must obtain subscriptions or API access from their selected model providers.

Roadmap transparency

Direct model offerings, token controls, templates, and integrated application deployment are planned capabilities and are not yet generally available.

Ready to move forward?

Deploy with confidence, or talk to an engineer first.

Review pricing, browse the live catalog, or contact Seemi Cloud for migration and enterprise engineering support.

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SERVICE AT A GLANCE

Key technical and operational facts

Concise deployment facts for evaluation. The portal configuration and applicable SKU description remain authoritative.

Workload: AI software-engineering workspace
User access: HTTPS web interface
Authentication: Seemi forward authentication
Model access: Customer-provided compatible provider credentials
Workspace: Persistent path according to selected tier
Backup: Restic on eligible workspace files
Model tokens: Not included in current Seemi pricing
Security model: Treat as a privileged development environment

FREQUENTLY ASKED QUESTIONS

Practical answers before deployment

Understand connectivity, backups, limitations, and operating responsibilities before selecting a SKU.

Does Seemi include AI model tokens?

No. Seemi currently provides the OpenHands runtime. Customers obtain model access from a compatible provider or use an approved local or remote model endpoint.

How is the OpenHands interface protected?

The browser interface uses Seemi forward authentication with supported Microsoft or Google identity. Repository credentials, model keys, and workspace secrets still require separate protection.

What can OpenHands do?

OpenHands can inspect repositories, edit files, use development tools, run tests, investigate errors, and support agentic development workflows, subject to the configured model and workspace permissions.

Are workspaces persistent and backed up?

Eligible workspace files are stored on the configured persistent path and can use Restic snapshots. External source-control systems and model-provider records require their own protection.

Is generated code automatically safe to deploy?

No. AI-generated changes require code review, tests, dependency review, secret scanning, and ordinary software security controls before deployment.

How should repository credentials be scoped?

Use a dedicated credential with minimum repository and branch permissions. Avoid placing broad production credentials or cloud administrator secrets in the workspace.

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