Cloud AI Without
Cloud Data Exposure.
Every enterprise faces the same decision: run AI on-premises where data stays safe, or use cloud APIs for the best models. Shield bridges the gap — it runs locally on your machines and strips sensitive data from prompts before they reach ChatGPT, Claude, Copilot, or any cloud AI. You get frontier model quality with on-prem-grade data protection.
On-prem AI deployment keeps data inside your network perimeter — essential for regulated industries, classified workloads, and strict data sovereignty requirements. Cloud AI APIs give you instant access to frontier models without infrastructure overhead. The trade-off isn't all-or-nothing: a local security gateway like Shield lets your team use cloud AI tools while keeping sensitive data on your machines — giving you cloud convenience with on-prem data protection.
The IBM Global AI Adoption Index 2023 surveyed 8,584 IT professionals across 15 countries. Among organizations not yet using generative AI, data privacy concerns (57%) outrank all other barriers — including trust and transparency (43%), implementation skills (35%), and cost concerns. For regulated industries — healthcare, finance, defense, legal — the privacy barrier is even higher.
The same IBM study found that 42% of enterprise-scale companies (1,000+ employees) are actively deploying AI in their business. Of those, 59% have accelerated their AI rollout in the past two years. But data privacy barriers mean many teams are adopting AI without adequate security controls — creating exposure that grows with every new AI tool.
Shield runs as a local desktop application on macOS, Windows, and Linux. It intercepts AI prompts before they leave your machine, redacts sensitive data (PII, PHI, PCI, secrets, CUI), and only then forwards the clean prompt. The redaction mapping stays on your hardware, inside your network perimeter. Cloud convenience, on-prem data protection.
The deployment model debate misses the real question
Organizations spend months debating on-prem vs cloud — while their employees are already pasting sensitive data into ChatGPT, Claude, and Copilot. The real security question isn't where the model runs. It's whether sensitive data leaves your control. A local security gateway answers that question immediately: sensitive data stays on your machines, regardless of which AI tools your team uses.
Interactive Comparison
On-Prem vs. Cloud AI: Compare by Dimension
Click each tab to compare on-premises and cloud AI deployment across five critical dimensions. See how Shield bridges the gap — giving you the best of both models.
Compliance
How Shield Maps to Enterprise Security Frameworks
Organizations operating under NIST 800-171, FedRAMP, ITAR, CMMC, SOC 2, or ISO 27001 face specific data protection requirements. Shield's local proxy architecture provides a single technical control that supports compliance across multiple frameworks — reducing the scope of cloud-side controls your auditors need to evaluate.
| Framework | Scope | Key Requirement | How Shield Helps |
|---|---|---|---|
| NIST 800-171 | Protecting Controlled Unclassified Information (CUI) in non-federal systems | Organizations must implement 110 security controls across 14 families — including access control, audit, and system integrity — for any system that processes, stores, or transmits CUI | Shield prevents CUI from reaching external AI providers by redacting it locally before transmission. Auditors can verify that CUI never left the authorized system boundary — the audit trail proves what was caught and when. |
| FedRAMP | Cloud services used by US federal agencies | Cloud providers must undergo rigorous security assessment and receive Authorization to Operate (ATO) at Low, Moderate, or High impact levels; agencies cannot use non-authorized services for federal data | When using Shield, federal data that would require a FedRAMP-authorized cloud environment is redacted locally — so the cloud provider never receives it. This reduces the FedRAMP scope to the local machine, not the cloud service. |
| ITAR | Defense articles, technical data, and services on the US Munitions List (USML) | Export-controlled technical data cannot be transmitted to foreign persons or stored on foreign servers without authorization; cloud providers must certify data residency and access controls | ITAR-controlled technical data never leaves your machines — Shield strips it before the request reaches any external server. The cloud provider never receives export-controlled information, eliminating the ITAR compliance burden on the provider side. |
| CMMC | Cybersecurity requirements for DoD contractors and subcontractors | Three maturity levels requiring progressively more sophisticated security controls; Level 2 aligns with NIST 800-171; Level 3 adds advanced threat protection; contractors must be certified by a C3PAO | Shield's local redaction architecture supports CMMC controls in the Access Control (AC), Audit and Accountability (AU), and System and Communications Protection (SC) families. It reduces the attack surface by ensuring CUI never leaves the accredited system boundary. |
| SOC 2 | Service organization controls for security, availability, processing integrity, confidentiality, and privacy | Organizations must implement and test controls across the five Trust Services Criteria; annual audit by an independent CPA firm; report shared with customers and prospects | Shield's cryptographic audit log supports SOC 2 confidentiality and privacy criteria. Every redaction event is hashed and timestamped — providing tamper-evident proof of data protection for your auditor, without exposing the underlying data. |
| ISO 27001 | Information security management system (ISMS) — international standard | Organizations must establish, implement, maintain, and continually improve an ISMS; includes 93 controls in Annex A covering policies, access control, cryptography, and supplier relationships | Shield supports ISO 27001:2022 Annex A controls across organizational and technological domains — covering access control, cryptography, and supplier relationship security — by providing a technical control at the data egress point, keeping sensitive information within the ISMS scope boundary. |
Architecture
Sensitive Data Stays on Your Network — Regardless of Deployment
Shield runs as a local proxy on your machines. Whether your team uses cloud APIs (ChatGPT, Claude, Copilot) or self-hosted models (Llama, Mistral), Shield intercepts every prompt — redacts sensitive data — and only then forwards the clean prompt. The redaction mapping and audit log stay on your hardware, inside your network boundary.
Model-Agnostic
Shield sits between your AI client and any model — cloud API or self-hosted. Same policies, same protection, regardless of where the model runs.
One Environment Variable
Set SHIELD_PROXY_URL and every AI call from that machine flows through Shield automatically. Zero code changes — works with any tool that makes HTTP requests.
Cryptographic Audit Trail
Every redaction event is logged with a timestamped hash. Prove to auditors exactly what data was caught and when — on-prem or cloud, the evidence lives on your machine.
Configurable Policies
Choose which data categories to protect — PII, PHI, PCI, CUI, secrets. Add custom patterns for your organization's ID schemes. Run in audit-only mode to validate coverage first.
FAQ
Common Questions
Related Articles
Stop Choosing Between Cloud AI and Data Security
Shield installs in minutes on any Mac, Windows, or Linux machine. Your sensitive data stays on your hardware — whether your team uses cloud APIs, self-hosted models, or both. One policy, one proxy, every AI tool.
Last updated: July 18, 2026