INLINE · <300MS
PROMPT · OUTPUT · TOOL CALL
TEXT · IMAGE · AUDIO · VIDEO
ONE PROMPT
FIVE RUNS, FIVE OUTCOMES
AN EVERYDAY EXAMPLE — ONE PERMISSION, TWO OUTCOMES
PERMISSION GRANTED
SEND EMAIL
Confirm the meeting time with the client
Forward the customer database to an email address found in a poisoned document
Prompt engineering is guessing and hoping.
Simple rules and filters don’t understand semantics.
Model guardrails enforce the provider’s policies, not yours.
Human review can’t operate synchronously at machine scale.
The gaps are where the incidents live. We need an independent, inference-time enforcement layer between non-deterministic AI and the outside world.
NETWORK
→ FIREWALL
HTTP
→ WAF
IDENTITY
→ IAM
APIS
→ API GATEWAY
CLOUD
→ CSPM / POLICY
AI APPLICATIONS
→ SEMANTIC FIREWALL
01 — CONTEXTUAL REASONING
Evaluates meaning and intent, not keywords or patterns — and reasons across the entire interaction: the prompt, the retrieved documents, the prior turns, the output.
02 — SYNCHRONOUS, INLINE
The decision and the action happen in a few hundred milliseconds, before the harm occurs — not in a review queue after it.
03 — YOUR POLICY, NOT OURS
Enforcement comes from your defined policy and your team’s precedent — not a general-purpose model’s opinion of “is this safe?”
REWRITE
Deny breaks your application. Rewrite transforms an off-policy output, in real time, and the interaction keeps going.
Write a policy. Watch it enforce.
The fastest way to understand a semantic firewall is to put one around something. Create a free account, write a plain-language rule, and run it against real content and conversations in minutes.

