Architecture guide
LLM security architecture diagram for enterprise AI control layers.
A useful LLM security architecture diagram shows where policy runs before prompts reach providers. PromptWall frames that architecture as a LLM security platform with prompt firewall, AI DLP, gateway, and audit layers working together.
Control
Policy first
Map every AI interaction to allow, flag, mask, or block decisions.
Data
DLP aware
Detect sensitive prompts, regulated data, and document leakage risk.
Traffic
Gateway aligned
Apply controls before prompts reach external model providers.
Evidence
Audit ready
Keep explainable records for security, risk, and compliance reviews.
Diagram
The enterprise LLM security layer has six control points.
Think of the architecture as a flow: user or app request, identity and surface context, prompt firewall inspection, AI DLP masking, policy decision, provider gateway routing, and audit evidence. This gives buyers a diagram they can explain to CISOs, platform teams, and compliance owners without reducing AI security to one detector.
Entry
1. Capture surface
Browser AI, app traffic, gateway requests, and agent/tool activity are normalized into security events.
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Inspection
2. Prompt firewall
Unsafe instructions, injection attempts, jailbreaks, and suspicious prompt intent are evaluated before dispatch.
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Data
3. AI DLP
Sensitive data, regulated records, credentials, and document leakage risks are masked, flagged, or blocked.
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Traffic
4. Gateway policy
Model provider routing is governed with consistent decisions across OpenAI, Azure, Anthropic, Gemini, and internal routes.
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Evidence
5. Audit trail
Security teams get evidence of the input, risk category, policy action, and final allowed or sanitized request.
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Governance
6. Review loop
Flagged interactions become governance feedback for policy tuning and enterprise rollout.
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Buyer use
Use the diagram to separate platform coverage from point-tool claims.
A vendor may cover one box well. Enterprise buyers need to know whether the vendor covers the full control path from prompt intake to provider routing and audit. Use this page alongside the enterprise AI security solutions comparison.
Map your AI traffic to an LLM security architecture
Review your AI surfaces, providers, sensitive data paths, and audit needs with PromptWall.
Frequently asked questions
What should an LLM security architecture include?+
It should include capture surfaces, prompt inspection, AI DLP, policy decisions, provider routing, audit evidence, and governance review loops.
Is this the same as a normal API architecture?+
No. LLM security architecture must inspect natural language prompts, retrieved context, sensitive data, model routes, and governance outcomes.