OnDevice Secure™
Know which AI workflows need stronger privacy protection — and how to deploy them safely.
Why this exists.
Businesses are entering confidential, sensitive, and proprietary information into public AI systems without understanding how that data is stored, who can access it, or how prompt retention creates exposure. Most public AI tools were not designed for regulated workloads.
PHI in a public chatbot
A clinician pastes patient notes into a public LLM for summary. The retention policy is unclear. HIPAA exposure is real.
M&A diligence in a free tier
A junior associate pastes a target's financials into a free AI tool. The data may now be in training pipelines or third-party logs.
Source code through a public API
Engineering uses an unapproved AI coding assistant. Proprietary algorithms now exist outside the firm's perimeter.
Capabilities
Private AI workflow consulting
Identify which workflows must move off public models.
Localized AI infrastructure strategy
On-device, on-premise, and isolated cloud deployment options.
Operational privacy recommendations
Prompt hygiene, data classification, and retention boundaries.
Secure workflow planning
Right-sized review and approval gates for sensitive use cases.
Sensitive data handling guidance
PHI, PII, IP, and regulated data segmentation.
AI deployment recommendations
Vendor selection criteria tuned to your risk profile.
Sensitive data is entering public AI systems. Leadership has no visibility into what or how much.
A tiered AI workflow map: which use cases can stay on public tools, which need private deployment, and how to migrate.
Feeds your Sentinel Score™
OnDevice Secure™ informs the Data Privacy dimension of your Sentinel Score™ and shapes deployment recommendations in your action plan.