Shadow AI
Public tools used outside corporate policies create security and compliance blind spots.
AI governance infrastructure
AI without governance is just chaos. Cortex is control.
Cortex brings together +65 AI models in an enterprise infrastructure with policies, traceability, security and visibility to scale AI with control.
- Governance layer
- Usage policies
- Security boundary
- Data protection
- Acceleration engine
- Observability
Companies that trust Cortex
The problem
The risk is not using AI. It is using it without control.
Rapid adoption of AI tools without a governance layer creates security, compliance and operational blind spots. Without visibility, the organization cannot scale responsibly.
Sensitive data exposure
Prompts, documents and strategic information can be sent to external models without traceability.
Incomplete audits
Without reliable records, it becomes difficult to identify who used AI, what was processed and which decisions were made.
Costs without visibility
Fragmented use of APIs and tools reduces predictability and makes AI investment decisions harder.
Enterprise infrastructure
Governance, security and acceleration on a single platform.
Governance layer
Defines clear rules for AI use, establishes responsibilities and creates auditable decisions aligned with the business.
Security boundary
Protects data, prompts and interactions through policies applied before, during and after processing.
Acceleration engine
Brings AI into processes and workflows to turn technological capacity into measurable impact.
Power with control
+65 AI models. One governance infrastructure.
Cortex provides access to and orchestration of models from different providers without giving up policies, visibility, traceability or security.
+65+65 AI models
Access models from different providers on a single platform.
Governance by design
Auditing, visibility and control are part of the operational foundation.
Data control
Data, prompts and interactions remain subject to policies defined by the organization.
Enterprise security
Architecture prepared for critical environments and enterprise requirements.
The current Cortex catalog includes proprietary and open source models validated for the platform.
Capabilities
A central layer to govern AI across the organization.
Model catalog and orchestration
Select and route models according to task, policy, risk and context.
Usage policies
Define who can use AI, which models are allowed and for what purposes.
Access control
Apply RBAC, ACLs, profiles, groups and contextual rules.
Data protection
Classify information, apply filters and reduce exposure of sensitive data.
Audit trails
Record users, models, processed data, decisions and results.
Observability
Monitor usage, costs, volume, performance and relevant events.
AI risk management
Identify, classify and treat risks associated with enterprise adoption.
Agents and integrations
Connect authorized workflows, tools and systems to a governed infrastructure.
Consolidated platform
Model orchestration with enterprise context.
Cortex combines models, agents, knowledge and workflows in a centralized experience for users and administrators.
How it works
Governance applied throughout the AI journey.
Cortex connects sources, data, systems and interfaces to a central governance layer. Every interaction passes through policies, filters, access controls and records before reaching models, agents or enterprise integrations.
- 01
Input
Requests arrive from users, systems, APIs or interfaces.
- 02
Sources and context
Cortex connects authorized documents, databases, applications and enterprise sources.
- 03
Policies and filters
Access, classification, DLP, context and compliance rules are applied.
- 04
Processing
The platform orchestrates AI models, agents and tools as needed.
- 05
Integrations
Responses can feed authorized enterprise systems, workflows and channels.
- 06
Controlled output
The result is filtered and delivered according to defined policies.
- 07
Audit
The interaction creates history, traceability and governance evidence.
Bring governance and control to your organization's AI adoption.
The difference is in the adoption model
Isolated AI creates exposure. Governed AI enables scale.
AI without governance
- Tools scattered across multiple areas.
- Models used without enterprise criteria.
- Data without consistent protection.
- Limited traceability.
- Fragmented costs.
- Reactive and manual auditing.
- Improvised integrations.
- Expansion without standards.
Operations with Cortex
- Centralized access to authorized models.
- Policies applied consistently.
- Control of context, permissions and data.
- Complete audit trails.
- Visibility into usage and costs.
- Continuous evidence for compliance.
- Integration with enterprise architecture.
- Scale with governance.
Outcomes
More productivity. Less exposure. Decisions with context.
Productivity at scale
Bring AI into workflows without proportionally increasing operational exposure.
Operational efficiency
Automate processes and reduce repetitive tasks on a governed foundation.
Cost control
Monitor usage by area, model, user or task type to guide investments.
Risk reduction
Structure policies, traceability and data protection to reduce legal and reputational exposure.
Maturity
Governance evolves with your organization.
Controlled adoption
Basic visibility and centralized access for organizations that are getting started.
Enterprise governance
Policies, audits, integrations and granular control for operations at scale.
Sovereignty and critical infrastructure
Dedicated environments, advanced controls and isolation for maximum security requirements.
Observability
Measurable control, value and governance.
Control
- User telemetry.
- API telemetry.
- Access channels.
- Models used.
- Profiles and groups.
Value and efficiency
- Conversation volume.
- Messages processed.
- Files analyzed.
- Consumption by area.
- Costs by model.
Governance
- Audit trails.
- Decision history.
- Traceability.
- Compliance evidence.
- Alerts and applied policies.
AI sovereignty
Your data remains under your control.
Cortex was designed for organizations that need to adopt AI without giving up security, visibility or enterprise accountability.
Customer data
Data remains under the organization's control.
Governance by design
Policies, traceability and responsibilities are part of operations, not an add-on.
Enterprise security
Architecture prepared for critical environments, integrations and internal requirements.
Compliance evidence
Records, reports and history support auditing and compliance processes.
The assets above identify standards, laws and references considered by platform controls. Their display does not, by itself, represent certification or automatic compliance.
Frequently asked questions
What technology and security leaders need to know.
What is Shadow AI and how does Cortex help control it?
Shadow AI is the unauthorized use of AI tools. Cortex centralizes access in a governed environment with authorized models, policies and visibility to reduce blind spots.
How do Cortex audit trails work?
Each interaction can record the user, time, model, processed data and result. These records support traceability, investigations and internal or external audits.
Is company data used to train models?
Customer data remains the customer's and is not used by Cortex to train models.
Does Cortex provide controls for LGPD and other standards?
Cortex provides controls and evidence that support compliance programs for LGPD, GDPR, ISO 27001 and internal standards. Final compliance depends on the organization's implementation, processes and responsibilities.
How does Cortex help control AI costs?
Telemetry organizes consumption by user, area, model and task type. This visibility supports cost allocation, waste identification and investment decisions.
Which AI models does Cortex support?
Cortex supports +65 AI models from different providers, including proprietary and open source options, according to the platform's current catalog.
How does Cortex adapt to organizational maturity?
Operations can evolve from controlled adoption to enterprise governance and sovereignty with critical infrastructure, expanding policies, integrations and isolation as needed.
Insights
Content on governance and responsible AI adoption.
AI in cybersecurity: evaluating a pilot while controlling risk
A practical approach to selecting an AI use case, protecting data and measuring results before expanding automation in a security team.
Read article: AI in cybersecurity: evaluating a pilot while controlling risk
Responsible business AI: turning principles into verifiable decisions
Ownership, evaluation, review channels and monitoring: organize governance for an AI use case beyond a written policy.
Read article: Responsible business AI: turning principles into verifiable decisions
Cortex 0.6.34: a historical record of documents, security and UX
What the October 2025 publication recorded about MinerU, JWT tokens, synchronization and translations, with checks for your environment.
Read article: Cortex 0.6.34: a historical record of documents, security and UXGovernance to accelerate with control
It is not about using AI. It is about mastering it.
Turn AI from an operational risk into strategic infrastructure for your organization.