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The First Enterprise Platform for
Operationalizing Built-In Cloud Security Controls Across Multi-Cloud

The Cloud Security
Control Plane for the Enterprise

Define intent once, assess impact before rollout, and enforce consistent guardrails across AWS, Azure, Google Cloud, and OCI from a single operational layer

Schedule a Demo

How Native Works

AWS

Azure

Google Cloud

Oracle Cloud

Built for the full cloud control lifecycle

Native gives teams one platform to define outcomes, deploy controls, validate impact, and manage changes as cloud environments evolve.

Enforcement at the source

Secure by Design Cloud Architecture

Build and maintain cloud environments that are secure by design.

Define mandatory security outcomes that are enforced workloads are deployed
Enforce data perimeter, least privilege, AI governance, and exposure restrictions by default
Validate effective enforcement coverage across accounts and providers
Implement controls using native cloud enforcement mechanisms

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Enforcement at the source

Secure by Design Cloud Architecture

Build and maintain cloud environments that are secure by design.

Define mandatory security outcomes that are enforced workloads are deployed
Enforce data perimeter, least privilege, AI governance, and exposure restrictions by default
Validate effective enforcement coverage across accounts and providers
Implement controls using native cloud enforcement mechanisms

+ Show more

INTENT TO ENFORCEMENT

Intent-Driven Cross-Cloud Guardrails

Define security outcomes once and generate provider-native enforcement across multiple clouds.

Express required security outcomes in structured natural language
Generate provider-specific enforcement controls with cross-cloud equivalence visibility
Unified outcome model spanning AWS, Azure, Google Cloud, and OCI
Consistent enforcement despite differences in provider control frameworks
Deploy guardrails directly, export as code, or follow guided implementation
Central visibility into control coverage and enforcement gaps

+ Show more

INTENT TO ENFORCEMENT

Intent-Driven Cross-Cloud Guardrails

Define security outcomes once and generate provider-native enforcement across multiple clouds.

Express required security outcomes in structured natural language
Generate provider-specific enforcement controls with cross-cloud equivalence visibility
Unified outcome model spanning AWS, Azure, Google Cloud, and OCI
Consistent enforcement despite differences in provider control frameworks
Deploy guardrails directly, export as code, or follow guided implementation
Central visibility into control coverage and enforcement gaps

+ Show more

Confident enforcement

Impact Analysis

Assess policy impact before and after enforcement deployment.

Replay historical cloud activity to model potential enforcement impact
Test desired enforcement logic against current identity and resource configurations
Receive tailored policy rollout recommendations to minimize operational disruption
Post-deployment visibility into blocked actions and affected identities

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Confident enforcement

Impact Analysis

Assess policy impact before and after enforcement deployment.

Replay historical cloud activity to model potential enforcement impact
Test desired enforcement logic against current identity and resource configurations
Receive tailored policy rollout recommendations to minimize operational disruption
Post-deployment visibility into blocked actions and affected identities

+ Show more

Continuous operational control

Native Security Operationalization

Sustain and adapt your secure-by-design guardrails as environments evolve.

Detect and visualize policy drift when guardrails are changed outside approved processes
Update installed policies in response to evolving business requirements or cloud provider changes
Managed exception handling with documented approvals and expiration
Full traceability of control changes and enforcement state over time

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Continuous operational control

Native Security Operationalization

Sustain and adapt your secure-by-design guardrails as environments evolve.

Detect and visualize policy drift when guardrails are changed outside approved processes
Update installed policies in response to evolving business requirements or cloud provider changes
Managed exception handling with documented approvals and expiration
Full traceability of control changes and enforcement state over time

+ Show more

Continuous enforcement feedback

Integrated Enforcement Lifecycle

Integrate security enforcement and feedback directly into engineering workflows.

Real-time notifications of blocked actions via collaboration tools such as Slack or Teams
Clear explanation of why an action was blocked and what change is required
Built-in workflow for submitting and tracking change requests
Visibility into recurring enforcement friction to inform control updates

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Continuous enforcement feedback

Integrated Enforcement Lifecycle

Integrate security enforcement and feedback directly into engineering workflows.

Real-time notifications of blocked actions via collaboration tools such as Slack or Teams
Clear explanation of why an action was blocked and what change is required
Built-in workflow for submitting and tracking change requests
Visibility into recurring enforcement friction to inform control updates

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AI Architecture Controls

AI Enforcement at the Source

Control how AI services are provisioned, accessed, and governed with secure-by-design enforcement within the cloud.

Enforce which AI/ML services can be provisioned (by OU, subscription, project)
Enforce which models can be used and deployed; approval workflows for new model types
Prevent AI services from accessing sensitive data, including PII in prompts
Enforce metadata/telemetry controls: prevent providers from training on your data
Cross-cloud consistency across AWS Bedrock, Azure OpenAI, GCP Vertex AI
AI service cost governance: spend limits and approval gates

+ Show more

AI Architecture Controls

AI Enforcement at the Source

Control how AI services are provisioned, accessed, and governed with secure-by-design enforcement within the cloud.

Enforce which AI/ML services can be provisioned (by OU, subscription, project)
Enforce which models can be used and deployed; approval workflows for new model types
Prevent AI services from accessing sensitive data, including PII in prompts
Enforce metadata/telemetry controls: prevent providers from training on your data
Cross-cloud consistency across AWS Bedrock, Azure OpenAI, GCP Vertex AI
AI service cost governance: spend limits and approval gates

+ Show more

Security Outcomes, Enforced Across Clouds

Explore the policy domains teams most commonly run to deliver consistent, provider-native enforcement across clouds.

Data Perimeter

Enforce boundaries on where data can reside, how it can be accessed, and how it can move.

AI Governance

Control how AI services are used in the cloud, including access to personal data, model permissions, and whether cloud providers can train on your metadata.

Attack Surface Management

Restrict unnecessary use of cloud services and regions to reduce monitoring burden, support compliance, and enforce data residency requirements.

Least Privilege

Continuously enforce minimum access rights for human and machine identities based on business requirements.

Blast Radius Containment

Define and validate isolation boundaries so the compromise of one resource, account, or workload cannot cascade.

Configuration Baselines

Define and enforce non-negotiable security configuration standards across cloud environments.