Enterprise AI security architecture
A reference architecture for securing LLM deployments at enterprise scale. Four layers — interception, detection, policy, and integration — provide defense-in-depth for AI interactions across every surface.
Why AI needs a dedicated security architecture
Existing security architecture — firewalls, WAFs, DLP, CASB — was designed for web applications and network traffic. AI interactions introduce a new data plane that bypasses these controls. AI security differs fundamentally from traditional AppSec in threat model, inspection requirements, and enforcement patterns.
Four-layer architecture
01
Interception Layer
Capture AI interactions at the point of use — browser extension, editor plugin, CLI proxy, or ICAP gateway. Provider-agnostic capture across all AI access surfaces.
02
Detection Layer
Multi-engine inspection: PII entity recognition, injection ML classification, document similarity analysis, toxicity scoring, and custom pattern matching.
03
Policy Layer
Tenant-configurable rules that map detection results to enforcement actions. Allow, mask, flag, or block based on thresholds, data types, and user roles.
04
Integration Layer
Connect to existing infrastructure: SIEM/SOC (Splunk, Elastic), identity providers (SAML/OIDC), and compliance reporting systems.
Multi-surface deployment
Enterprise AI usage spans multiple surfaces that must all be governed by the same security policy:
- Browser — Chrome extension intercepts ChatGPT, Claude, Gemini at the DOM level
- Editor — VS Code / Cursor integration inspects Copilot code context
- CLI — Local proxy captures
curl, Python scripts, and programmatic API calls - Gateway — ICAP integration with Zscaler / Squid for network-level AI traffic routing
Multi-tenant design
PromptWall is built multi-tenant from the ground up. Each tenant has isolated policies, detection thresholds, protected document corpora, and audit trails. This enables MSPs and large enterprises with multiple business units to operate independently within the same platform.
Integration patterns
AI security does not operate in isolation. PromptWall integrates with existing enterprise infrastructure through SOC connectors (Splunk HEC, Elastic Bulk, webhook), identity federation (SAML, OIDC), and audit trail exports for compliance reporting.
Deploy enterprise AI security
See PromptWall's architecture in action with a guided demo.
Frequently asked questions
What is the minimum viable AI security architecture?+
At minimum: a prompt inspection layer (detecting PII and injection), an audit trail for compliance, and a policy engine for governance. PromptWall provides all three in a single deployment. Additional layers (SOC integration, document protection, multi-provider routing) can be added incrementally.
How does AI security architecture differ from traditional AppSec?+
Traditional AppSec secures code and infrastructure. AI security secures data flows and interactions — the prompts users send and the responses they receive. The threat model is fundamentally different: data exfiltration through natural language rather than code exploitation.
Can I deploy AI security incrementally?+
Yes. Start with browser extension deployment for immediate ChatGPT/Claude protection. Add editor integration for Copilot. Then deploy CLI proxy for API coverage. Each surface uses the same policy engine, so security is consistent from day one.