+What ai gateways are
AI gateways sit between your apps and model providers to route, load-balance, cache, rate-limit and meter LLM traffic. Some add basic content filters.
+Side by side
Capability by capability
| Capability | AI gateways | Intertrace |
|---|---|---|
Route and load-balance model traffic Intertrace's edge is built on an open-source gateway. | ✓ | ✓ |
Rate limits and usage metering | ✓ | ✓ |
Prompt-injection and jailbreak detection Rules, intent and an AI judge fused into one decision. | Partial | ✓ |
Authorize tool calls before they execute | — | ✓ |
Human approval with single-use execution permits | — | ✓ |
MCP tool inspection and schema pinning | Partial | ✓ |
Per-agent inventory and attack graph | — | ✓ |
Decision evidence for reviewers | Partial | ✓ |
“AI gateways” describes the typical category, not a specific product. Individual products vary.
+Honest answer
Which do you need?
+AI gateways alone is enough when
- You need routing, fallbacks and cost control across providers
- Your AI features are read-only chat with no tools or data access
- No one needs to review or evidence individual decisions
+You need a decision layer when
- Agents call tools, touch customer data or take actions
- You need to stop a request before it runs, not just log it
- Security or audit teams ask why a specific action was allowed
+Better together
Already running a gateway? Keep it. Intertrace can sit in front of it or behind it; the decision layer doesn't care what routes the bytes.
+Other comparisons
+ The AI watching your AI
Run the comparison on your traffic.
Bring your own prompts and tool calls. We'll show what each approach decides.