Enforcement vs Observability — why watching costs after they happen isn't enough.
Helicone is an observability platform. It tracks your LLM API calls, logs token usage, and shows you dashboards of what already happened. It's excellent for understanding costs after they've been incurred.
AgentShield is an enforcement engine. It evaluates each API call against spend rules before it executes. If a transaction violates a rule — transaction limit, daily cap, velocity threshold — it's blocked instantly in under 1ms.
Check Your Risk Score →| Capability | AgentShield | Helicone |
|---|---|---|
| Block transactions before execution | ✅ <1ms eval | ❌ After-the-fact only |
| Transaction limit rules | ✅ Per-call limits | ❌ Not supported |
| Daily spend caps | ✅ Per-agent caps | ❌ Alerts only |
| Velocity detection | ✅ Rolling window | ❌ Not available |
| Merchant allowlists | ✅ Approved providers only | ❌ Not available |
| Category blocks | ✅ Crypto, gambling, etc. | ❌ Not available |
| Real-time SSE alerts | ✅ Instant block notifications | ✅ Webhooks |
| API call logging | ✅ Decision audit trail | ✅ Full request logging |
| Request/response inspection | ❌ Not a debugging tool | ✅ Core feature |
| Token-level cost breakdown | ❌ Focus is prevention | ✅ Detailed analytics |
| Zero dependencies | ✅ Python stdlib only | ❌ Requires SDK + dependencies |
| Self-hostable in 60s | ✅ Single Docker image | ❌ Complex setup |
You need to understand why costs are high. You want to inspect individual prompts and responses. You're debugging agent behavior and need full request/response logging.
You need to prevent costs from spiraling. You want hard limits that block transactions before they execute. You're running autonomous agents that could enter infinite loops or retry storms.
Route API calls through AgentShield for enforcement, then log to Helicone for observability. They solve different problems — AgentShield stops the bleeding, Helicone diagnoses it.
If an agent makes 21 API calls at $133 each in 60 seconds at 3 AM: