Problem solution
LLM guardrails with PromptWall.
PromptWall turns LLM guardrails from a policy concern into runtime controls across prompts, AI DLP, secure gateway traffic, and governance evidence.
Control
Policy first
Turn AI usage rules into runtime decisions.
Data
DLP aware
Detect sensitive data before prompts reach providers.
Evidence
Audit ready
Keep reviewable proof for security and compliance teams.
Traffic
Gateway aligned
Apply policy around provider and model traffic.
Problem definition
The problem
LLM guardrails are often implemented differently across teams and providers.
Risks
Why it matters
Inconsistent guardrails create gaps in prompt security, sensitive data handling, and auditability.
PromptWall solution
PromptWall applies policy before the AI interaction becomes risk.
PromptWall inspects AI prompts and context, detects sensitive content, applies allow/mask/flag/block policy, and preserves reviewable audit evidence.
Technical explanation
How the control path works
PromptWall centralizes guardrail decisions as policy actions across prompts, data, provider traffic, and audit.
Use case
Enterprise use case
A platform team can apply the same guardrail model across multiple AI applications.
Evaluate PromptWall for LLM guardrails
Bring your workflow, policy requirement, and sensitive data scenario. We will map the PromptWall control path.
Frequently asked questions
How does PromptWall help with LLM guardrails?+
PromptWall adds prompt inspection, AI DLP, gateway policy, and audit evidence at the point where AI usage happens.
Is this a replacement for existing security controls?+
No. PromptWall complements existing controls with AI-specific prompt, data, provider, and governance enforcement.