The Sub-millisecond Tool-Execution Firewall for Enterprise AI Agents. Cloud HTTP Gateways (like LangSmith) protect your LLM tokens. AEGIS protects your Stripe account and Crypto Wallets from asynchronous Agent Double-Spending.
When an autonomous agent enters a hyper-cognitive loop, it can fire hundreds of concurrent tool calls (e.g., Stripe API charges or Web3 transactions).
Cloud-based guardrails suffer from network latency (~50ms - 150ms). By the time the cloud gateway registers the budget depletion, the in-flight transactions have already drained your accounts.
AEGIS is a horizontal L3 Policy Gate designed purely for speed and state locking. It sits exactly between your Agent's reasoning engine and your execution tools.
- Sub-Millisecond Concurrency: High-Frequency Local IPC Memory Locks (
< 1ms) budget resolution. - Infrastructure Agnostic: Works with LangChain, AutoGen, CrewAI, or raw Python scripts.
- Zero Dependencies: No Redis, no Kafka. Pure Python in-memory atomic locks.
In a live stress test simulating a rogue agent attempting 1,000 concurrent Stripe tool calls:
- β 1000 concurrent requests intercepted
- β 0 double spends (Zero Financial Drift)
- β $50,000 overspend prevented
- β <0.001ms lock latency per request
pip install aegis-core-lortuarte-sdkπ οΈ Proof of Concept: The 3-Line Integration Wrap your high-risk tools (payments, trades, database writes) with the AEGIS gate.
# 1. Initialize local IPC Client
aegis_gate = PolicyGate(daily_budget_usd=100)
def execute_agent_payment(agent_id, amount):
# 2. Intercept budget spending BEFORE tool execution (<1ms lock)
decision = aegis_gate.evaluate_tool_execution(
agent_id=agent_id,
operation="stripe_charge",
amount=amount
)
if decision["status"] == "ALLOW":
# Safe to execute real API call
# stripe.Charge.create(...)
return "Transaction Authorized"
else:
# Loop blocked instantly. Budget saved.
return f"BLOCKED: Asynchronous Double-Spend Prevented in {decision['latency']}ms"
| Feature | LangSmith / Portkey (Cloud) | AEGIS Core (Local IPC) |
|---|---|---|
| Primary Target | Token Spend / Prompt Injection | Tool Execution / Money Spend |
| Latency | 50ms - 200ms (HTTP) | < 1ms (In-Memory) |
| Double-Spend Protection | Fails under high concurrency | Atomic deterministic locking |
Running autonomous agents in production?
Without runtime security, a single race condition can cause overspending, double-spends, and unsafe execution.
AEGIS Enterprise includes:
- π Policy dashboards
- ποΈ Real-time observability
- π€ Enterprise SLA support
- β‘ Custom infrastructure integrations
Book Enterprise Pilot at: https://aegis-api.com/
