Business AI Without
Giving Up Control of Your Data.

Consumer AI accounts are personal accounts managed by the provider, not by your organization. Your business has no control over which data is submitted, how it is retained by the provider, what access logging exists, or how accounts are managed when employees leave. Managed AI gives the organization a company-controlled environment with access management, data-protection controls, approved services, usage logging, and offboarding capability.

No. Many organizations use a combination of local AI processing for appropriate workloads and approved cloud AI services for tasks that require additional capability. The architecture is designed around your requirements, not a default configuration. Some organizations run entirely locally for data-isolation reasons. Others primarily use approved cloud AI services with data-protection controls in front of them.

Yes, where approved and configured. Managed AI can provide controlled access to approved cloud AI services while applying organizational data-protection policies, identity controls, and usage logging. Employees get the capability they need. The organization maintains control over which services are approved and what information can be submitted.

Configured data-protection controls can detect and protect supported categories of sensitive information before approved external processing occurs. This includes categories such as names, identification numbers, financial data, and other defined sensitive patterns. No detection system guarantees perfect accuracy on every input type in every context, and Edge Secure does not represent it as such. The controls meaningfully reduce the risk of sensitive data exposure; they do not eliminate all risk.

Yes, where configured and authorized. Approved company knowledge, including internal procedures, policies, technical documentation, and reference material, can be made available to the AI environment based on permissions. Different departments or user roles can have access to different knowledge sources according to organizational policy.

Part 11 applicability depends on the intended use of the AI system, the regulated records or processes involved, validation requirements, electronic signature considerations, and the controls applied. Edge Secure does not automatically represent any configuration as 21 CFR Part 11 compliant. For life sciences organizations, the security and technology considerations of a Managed AI deployment should be evaluated in the context of specific intended uses, applicable regulations, and validation obligations with qualified regulatory affairs professionals.

The deployment architecture and data-protection controls can be designed with the security requirements of healthcare environments in mind, including access controls, sensitive-data handling, and audit logging. Edge Secure does not automatically certify HIPAA compliance. Organizations subject to HIPAA should evaluate how AI is used in clinical or administrative workflows, what PHI is involved, and whether Business Associate Agreement obligations apply, in consultation with legal and compliance counsel.

Organization-controlled Managed AI access is managed as part of the employee offboarding process, the same way email and application access is handled. Access is removed when the employee departs. Consumer AI accounts that employees maintain independently cannot be managed or controlled by the organization at offboarding, which is one reason organizational control of AI access matters.

Deployment scope depends on the number of users, data sources being integrated, whether local infrastructure is included, integrations required, security requirements, and the complexity of use cases being configured. Edge Secure provides a timeline estimate after the initial readiness assessment. Simpler deployments can be operational within weeks. More complex environments with multiple integrations take longer.

Shadow AI refers to AI applications, accounts, and services that employees use without organizational approval, management, or visibility. This includes personal ChatGPT accounts, browser-based AI tools, and AI features embedded in unapproved SaaS applications. Shadow AI creates data exposure risks, inconsistent policies, no centralized logging, and unmanaged offboarding risk. Managed AI addresses shadow AI by providing a governed alternative that employees can actually use.