Security & Privacy

Your knowledge stays under your control.

Security choices should reflect the sensitivity of your information, your infrastructure and the AI providers selected for a deployment.

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Security philosophy

Neural Works favors clear deployment boundaries, least-necessary access and claims that can be verified for the configuration in use.

Deployment-aware controls

Security and privacy depend on the chosen architecture, provider and customer requirements.

No blanket guarantees

Specific controls and responsibilities are confirmed during solution design rather than implied universally.

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Deployment options

ATLAS Private

Customer-controlled infrastructure or private cloud can support data-sovereignty requirements, depending on storage, networking and AI-provider choices.

ATLAS Cloud

Managed deployment uses authentication, authorization and tenant-level controls to separate organizational knowledge.

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Identity, access and isolation

Authentication

Access is verified before protected organizational knowledge is made available.

Authorization

Permissions determine what authenticated users can access; the exact model depends on deployment configuration.

Tenant isolation

Tenant-level controls separate organizational knowledge in managed deployments.

Auditability

Expanded auditability is a roadmap area; requirements should be confirmed for each engagement.

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Data protection and lifecycle

Encryption in transit

Supported depending on deployment configuration and the services selected.

Encryption at rest

Supported depending on customer infrastructure, storage and managed-service configuration.

Storage and AI providers

Data location and provider handling depend on the architecture and chosen AI model provider.

Retention, deletion and backups

Policies are defined for the selected deployment; requirements and responsibilities are agreed before launch.

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Customer-controlled choices

Infrastructure

Private deployments can use infrastructure controlled by the customer.

Models

Architecture can be designed around an agreed AI-provider or privately hosted model strategy.

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